AI Show - Channel 9

On this very special episode of the AI Show, Seth is joined by high-school student, Saumya Soni who is here to showcase her creation, AI for Birds - a phone app that bird enthusiasts can use to predict the bird species name and learn more about the species. AI for Birds showcases Cognitive Services with Microsoft Custom Vision AI. Saumya is also the CEO of AI for Environment, a nonprofit on a mission to use technologies including AI, Internet of Things (IoT) and Business Intelligence to generate awareness of and solve global environmental challenges. Check it out! Jump to:[00:16] Seth welcomes Saumya Soni[01:20] Inspiration for AI for Environment[03:26] Demo - AI for Birds[06:10] How Saumya got started[08:36] Challenges training the model[10:00] How AI and IoT can enhance environmental sustainability Learn more:AI for Birds https://www.aiforbirds.com/AI for Environment https://aiforenvironment.org/Custom Vision Microsoft Azure https://aka.ms/AIShow/CustomVision Zero to Hero Machine Learning on Azure https://aka.ms/ZerotoHero/MLonAzureZero to Hero Azure AI https://aka.ms/ZerotoHero/AzureAIMachine Learning for Data Scientists https://aka.ms/AIShow/MLforDataScientistsPackt: Principles of Data Science https://aka.ms/AIShow/DataSciencePacktCreate a Free account (Azure) https://aka.ms/aishow-seth-azurefree Follow Seth https://twitter.com/sethjuarezFollow AI for Environment https://aka.ms/LinkedIn/AIforEnvironment Don't miss new episodes, subscribe to the AI Show https://aka.ms/AIShowsubscribe AI Show Playlist https://aka.ms/AIShowPlaylist Join us every other Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive

Krishna Doss and Mohamed Elghazali join Ayşegül Yönet to showcase how to break language barriers with Custom Translator, now supporting 100+ languages and dialects! Jump to:[00:16] Introductions[01:00] What problems does Translator address[02:01] Languages and dialects[02:53] Translator Compliance & Data Residency[05:05] Translator Challenges-Domain specific terminology-Accuracy and fluency-Adaptation-Time & cost[07:17] Do I need to be an AI specialist to create custom translations?[10:21] Demo - Custom Translator[14:13] Examples of quality data[26:49] Demo - Custom Translator new portal[29:10] Learn more Learn more:Ignite Data & AI https://aka.ms/IgniteDataAICustom Translation Blog https://aka.ms/CustomTranslationBlogCustom Translation Portal https://aka.ms/CustomTranslationPortalTranslator Docs https://aka.ms/AzureTranslatorDocsPython SDK Kit https://aka.ms/TranslationPythonSDK.NET SDK https://aka.ms/TranslatorDotNetSDKDocument Translation App Githubhttps://aka.ms/DocumentTranslationAppCodeZero to Hero Machine Learning on Azure https://aka.ms/ZeroToHeroMLZero to Hero Azure AI https://aka.ms/ZeroToHeroAzureAIMachine Learning for Data Scientistshttps://aka.ms/ZeroToHeroDataScientistPackt: Principles of Data Sciencehttps://aka.ms/PrinciplesOfDataScienceCreate a Free account (Azure) https://aka.ms/CognitiveServicesFree Follow Ayşegül https://twitter.com/AysSomethingFollow Bea https://twitter.com/beastollnitzBea's blog https://bea.stollnitz.com/blogFollow Krishna https://twitter.com/Krishna_DossFollow Mohamedhttps://www.linkedin.com/in/mohamed-el-ghazali-6863737/ Don't miss new episodes, subscribe to the AI Show https://aka.ms/AIShowsubscribeAI Show Playlist https://aka.ms/AIShowPlaylistJoin us every other Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive

On today's episode of the AI Show, Seth welcomes Swati Gharse who will show us how to build computer vision models using AutoML for Images! Jump to:[00:29] Welcome Swati[00:46] What kinds of problems Computer Vision solvesMulti-class image classificationMulti-label image classificationObject detectionInstance segmentation[02:15] Why is this so challenging?[03:18] AutoML feature capabilities[05:00] Supported algorithms and tunable hyperparameters[07:30] Demo: Training object detection model[08:33] Using default hyperparameter values for specified algorithm[11:46] Completed AutoML run[15:15] Custom Vision v. Computer Vision v. AutoML for Images[16:40] Learn more Learn more: AutoML Images Blog https://aka.ms/AIShow/AutoMLImages/Blog Zero to Hero Machine Learning on Azure https://aka.ms/ZerotoHero/MLonAzure Zero to Hero Azure AI https://aka.ms/ZerotoHero/AzureAI Machine Learning for Data Scientists https://aka.ms/AIShow/MLforDataScientistsPackt: Principles of Data Science https://aka.ms/AIShow/DataSciencePackt Create a Free account (Azure) https://aka.ms/aishow-seth-azurefree Follow Seth https://twitter.com/sethjuarez Follow Swatihttps://www.linkedin.com/in/swati-gharse-3781a97/ AI Show Playlist https://aka.ms/AIShowPlaylist Don't miss new episodes, subscribe to the AI Show https://aka.ms/AIShowsubscribe Join us every other Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive

On this episode of the AI Show, we're talking about MLOps. Seth welcomes Microsoft Data Scientist, Spyros Marketos, ML Engineer, Davide Fornelli and Data Engineer, Samarendra Panda. Together they make up an AI Taskforce and they'll give us a high-level intro into MLOps and share some of the surprises and lessons they've learned along the way!Jump to:[00:17] AI Show Intro[00:34] Welcome and Introductions[01:41] Use cases from the AI Taskforce[02:47] Commonalities across projects[03:50] Common challenges - from the Data Engineer perspective[06:47] Common challenges - from the ML Engineer perspective[08:46] Common challenges from the Data Science perspective[10:48] What does success in MLOps look like?[12:30] Surprising challenges working with customers and how to avoid them[19:27] Review - what is ML Ops[19:45] MLOps in Delivery mission[21:57] MLOps principles[27:52] Tips from the pros Learn more:Machine Learning for Data Scientists https://aka.ms/AIShow/MLforDataScientistsPakt: Principles of Data Science https://aka.ms/AIShow/DataSciencePacktZero to Hero Machine Learning on Azure https://aka.ms/ZerotoHero/MLonAzureZero to Hero Azure AI https://aka.ms/ZerotoHero/AzureAICreate a Free account (Azure) https://aka.ms/aishow-seth-azurefreeFollow Seth https://twitter.com/sethjuarezFollow Spyros https://www.linkedin.com/in/smarketos/Follow Davide https://www.linkedin.com/in/davidefornelli/Follow Sam https://www.linkedin.com/in/samarendra-panda/Don't miss new episodes, subscribe to the AI Show https://aka.ms/AIShowsubscribeAI Show Playlist https://aka.ms/AIShowPlaylistJoin us every other Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive

On this week's show, Seth welcomes grand prize winners of the 2021 OpenCV AI Competition. Satya Mallick from OpenCV is here with Ye Lu and Him Wai (Michael) Ng from Team Cortic Tigers, who will demo their award-winning project - Cortic Edge Platform (CEP) which aims to democratize AI for everyone!Jump to:[00:17] Welcome to the AI Show[01:01] What is the OpenCV AI Competition[03:15] 2021 Grand Prize Winner - Cortic Edge Platform (CEP) - allowing beginners and advanced programmers to start doing rapid AI prototyping[05:21] CEP use cases[10:01] Using Microsoft MakeCode to build CEP[13:34] What's next from OpenCV AI Learn more:OpenCV AI Competition https://opencv.org/opencv-ai-competition-2021/Cortic Technology GitHub repo https://github.com/cortictechnology/cepShop the OAK-D camera https://shop.luxonis.com/products/1098obcenclosure Kickstarter campaign https://www.opencv.org/kickstarterZero to Hero Machine Learning on Azure https://aka.ms/ZerotoHero/MLonAzureZero to Hero Azure AI https://aka.ms/ZerotoHero/AzureAICreate a Free account (Azure) https://aka.ms/aishow-seth-azurefreeFollow Seth https://twitter.com/sethjuarezFollow Satya https://twitter.com/LearnOpenCVFollow Cortic Technology https://twitter.com/CorticTechnolo1Follow Cortic Technology Group https://www.linkedin.com/company/cortic/Don't miss new episodes, subscribe to the AI Show https://aka.ms/AIShowsubscribeAI Show Playlist https://aka.ms/AIShowPlaylistJoin us every other Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive

Recorded live on September 10, 2021On this episode of the AI Show, Timm Walz joins Seth to talk about how ramping up your custom NLP tasks with Verseagility will benefit your data science workflow. He'll show us how to use the toolkit in combination with Azure Machine Learning. Be sure to check it out!Jump to:[00:27] Welcome Timm Walz[01:00] What is Verseagility[02:40] What does Verseagility include-standardized template for Infra as code-scripts-project conflicts[04:25] Demo[07:44] More about the data[11:42] Machine Learning tech stack[15:42] Learn more[16:35] Example ticketsLearn more:Github Microsoft Verseagility https://github.com/microsoft/verseagilityVerseagility Azure Websites https://verseagility.azurewebsites.netZero to Hero Machine Learning on Azure https://aka.ms/ZerotoHero/MLonAzureZero to Hero Azure AI https://aka.ms/ZerotoHero/AzureAICreate a Free account (Azure) https://aka.ms/aishow-seth-azurefreeFollow Seth https://twitter.com/sethjuarezFollow Timm https://twitter.com/nonstoptimm/Don't miss new episodes, subscribe to the AI Show https://aka.ms/AIShowsubscribeAI Show Playlist https://aka.ms/AIShowPlaylistJoin us every other Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive

On this episode of the AI Show, Seth welcomes back Lu Zhang! Lu will walk us through how to use the new prebuilt model in Azure Form Recognizer to extract key-value pairs from ID documents like passport and US driver's license, using the REST APIs, SDKs or low-code/no-code in AI Builder.Jump to:[00:17] Seth welcomes Lu Zhang[00:29] What is Form Recognizer?[01:17] What Form Recognizer does for ID documents?[01:52] What is an ID Doc?[02:53] How it works[03:45] What is FOTT?[04:40] Demo[09:10] How to do this in a low code, no code way[09:42] What is AI Builder?[10:21] ID flow Demo[11:47] Where to go to learn moreLearn more:Azure Form Recognizer Get Started https://aka.ms/AIShow/FormRecognizer/Get-StartedForm Recognizer Client Library SDKs https://aka.ms/AIShow/FormRecognizer/ClientLibrarySDKs Form Recognizer API doc https://aka.ms/AIShow/FormRecognizerAPI/DocPrebuilt ID doc https://aka.ms/AIShow/PrebuiltID/DocZero to Hero Machine Learning on Azure https://aka.ms/ZerotoHero/MLonAzureZero to Hero Azure AI https://aka.ms/ZerotoHero/AzureAICreate a Free account (Azure) https://aka.ms/aishow-seth-azurefreeFollow Seth https://twitter.com/sethjuarezFollow Lu Lu Zhang | LinkedInAI Show Playlist https://aka.ms/AIShowPlaylistDon't miss new episodes, subscribe to the AI Show https://aka.ms/AIShowsubscribeJoin us every other Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive

Join Seth as he welcomes Shivani Santosh Sambare to talk about Prebuilt Docker Images for Inference in Azure Machine Learning. Jump to:[00:17] Show begins[00:29] Welcome Shivani[00:38] What are the challenges working with ML environments?[01:11] Solutions to ML challenges/environments = Prebuilt Docker Images for Inference[02:12] How do I make this work with other specialized environments?[04:10] Demo: Deploying PyTorch model using Azure ML[04:30] Scoring script [06:50] End demo & recap[09:06] Learn more Learn more:Concept Prebuilt Docker Images: https://aka.ms/AIShow/PrebuiltDockerImages/AzureML/Doc Python Extensibility Solution: https://aka.ms/AIShow/PrebuiltDockerImages/PythonExtSolution Blog post: https://aka.ms/AIShow/PrebuiltDockerImages/TechComm/Blog Zero to Hero Machine Learning on Azure https://aka.ms/ZerotoHero/MLonAzureZero to Hero Azure AI https://aka.ms/ZerotoHero/AzureAICreate a Free account (Azure) https://aka.ms/aishow-seth-azurefreeAzure Machine Learning https://aka.ms/AIShow/AzureMLFollow Seth https://twitter.com/sethjuarezAI Show Playlist https://aka.ms/AIShowPlaylistDon't miss new episodes, subscribe to the AI Show https://aka.ms/AIShowsubscribe

In this episode of the AI Show, Edward Un is back and he's joined by Heiko Rahmel to talk about what's new in Speech to Text and Text to Speech. Landing the core scenarios for Speech service including speech transcription for call centers, text to speech for content creation, read-out functionality, and chatbots. Check it out!Jump to:[00:15] Seth welcomes Edward and Heiko[01:15] Speech to Text - What's new[02:30] Demo - Speech to Text[06:45] Pronunciation Assessment[09:35] Text to Speech - What's new[12:05] Cross Lingual Adaptation - Explore voice options[13:38] Demo - Custom voice[20:12] Ethics of Custom Neural Voice[22:23] Real-world uses: Speech to Text[24:34] Real-world uses: Text to Speech[26:00] Learn moreLearn more:ACOM page - https://aka.ms/AIShow/CognitiveSpeechServicesSpeech to text quickstart - https://aka.ms/AIShow/SpeechtoText/QuickstartText to speech quickstart - https://aka.ms/AIShow/TexttoSpeech/QuickstartBuild 2021 – Speech updates blog - https://aka.ms/AIShow/SpeechUpdates/BlogTranscribe speech blog - https://aka.ms/AIShow/TranscribeSpeech/BlogAzure speech and batch blog - https://aka.ms/AIShow/AzureSpeechandBatch/BlogBuild a voice blog - https://aka.ms/AIShow/BuildaVoice/BlogAI Show Playlist https://aka.ms/AIShowPlaylistCreate a Free account (Azure) https://aka.ms/aishow-seth-azurefreeGet Started with Machine Learning https://aka.ms/AIShow/StartMLAI for Developers - https://aka.ms/AIShow/AIforDevelopersAzure Machine Learning https://aka.ms/AIShow/AzureMLFollow Seth https://twitter.com/sethjuarezFollow Edward https://twitter.com/EdUnFollow Heiko https://twitter.com/HRahmelDon't miss new episodes, subscribe to the AI Show https://aka.ms/AIShowsubscribeJoin us every other Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive

On this episode from our #MSBuild recap, Gary Pretty is back to showcase the very latest in Azure Bot Service and demo how to build and deploy your bot in just a few steps!Jump to:[00:00] AI Show begins[00:25] Seth welcomes Gary[00:58] What's New with Azure Bot Service[03:02] Get Started with Composer[04:20] Authoring Conversational Experience[07:00] Enhanced testing and debugging[08:59] Extend your bot using package component[09:20] Teams-based bots[11:26] Bot Connections[13:31] Package Manager[16:17] Calendar capability with/Enterprise Assistant[19:38] Learn moreLearn more:Conversational AI Blog: https://aka.ms/AIShow/ConversationalAI/Build2021AI Show https://aka.ms/AIShowPlaylistCreate a Free account (Azure) https://aka.ms/aishow-seth-azurefreeGet Started with Machine Learning https://aka.ms/AIShow/StartMLAI for Developers https://aka.ms/AIShow/AIforDevelopersAzure Machine Learning https://aka.ms/AIShow/AzureMLFollow Seth https://twitter.com/sethjuarezFollow guest https://twitter.com/GaryPrettyDon't miss new episodes, subscribe to the AI Show https://aka.ms/AIShowsubscribeJoin us every other Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive

On this episode from our #MSBuild recap, Sethu Raman is here to highlight how Managed Endpoints provides out-of-box capabilities to operationalize models. Sethu will demo how to deploy and score a GPU model: highlighting dev experience with CLI & local deployment and how to perform safe rollout: highlighting metrics, log analytics integration.Jump to:[00:16] AI Show welcomes welcomes Sethu[00:38] How Managed Online Endpoints supports Azure Machine Learning[02:20] Intro to Endpoint concepts and deployments[03:16] Demo 1 - Deploy and score a GPU model[07:40] Demo 2 - Perform safe rollout[11:11] Deployment slots with different modelsLearn more:How do deploy Managed Online Endpoints: https://aka.ms/AIShow/HowToDeploy/ManagedEndpointsAI Show Live: https://aka.ms/AIShowCreate a Free account (Azure) https://aka.ms/aishow-seth-azurefreeGet Started with Machine Learning https://aka.ms/AIShow/StartMLAI for Developers https://aka.ms/AIShow/AIforDevelopersAzure Machine Learning https://aka.ms/AIShow/AzureMLFollow Seth https://twitter.com/sethjuarezFollow Sethu https://twitter.com/Sethu20Don't miss new episodes, subscribe to the AI Show https://aka.ms/AIShowsubscribeJoin us every other Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive

Check out this episode from our #MSBuild recap when Seth welcomed Krishna Doss back to the show to share the latest and greatest from Azure Translator, translating documents at scale and preserving formatting!Jump to:[00:17] Seth welcomes Krishna[00:59] What's new in Azure Translator[04:25] How it works[05:26] Sample requests[06:23] Source v. Translated docs[06:45] Demo[08:40] Developer experience[09:33] Learn moreLearn more:Document Translation user documentation https://aka.ms/AIShow/Translation/Doc Python Kit https://aka.ms/AIShow/PythonKit .NET Kit https://aka.ms/AIShow/NetKit Doc Translation in Translator https://aka.ms/AIShow/DocTranslationInTranslatorTranslator Microsoft Azure Pricing https://aka.ms/AIShow/AzureTranslator/PricingCreate a Free account (Azure) https://aka.ms/aishow-seth-azurefreeGet Started with Machine Learning https://aka.ms/AIShow/StartMLAI for Developers https://aka.ms/AIShow/AIforDevelopersAzure Machine Learning https://aka.ms/AIShow/AzureMLAI Show https://aka.ms/AIShowFollow Seth https://twitter.com/sethjuarezFollow Krishna https://twitter.com/Krishna_DossDon't miss new episodes, subscribe to the AI Show https://aka.ms/AIShowsubscribeJoin us every Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive

On this week's episode, Alon Bochman is here to talk about the exciting collaboration between PyTorch and Microsoft, PyTorch Enterprise on Microsoft Azure, and all that it has to offer! Jump to:[00:15] Seth welcomes Alon[01:04] What is PyTorch[01:41] Microsoft and PyTorch collaboration[02:57] What is PyTorch Enterprise on Microsoft Enterprise and what does it include?[03:39] Support[05:33] Testing[08:02] Integration[08:35] How to get involved[09:32] Partner feedback Learn more:PyTorch Enterprise on Microsoft Azure: https://aka.ms/AIShow/PyTorchEnterpriseonAzureRead more about the program on PyTorch: https://aka.ms/PTELandingPageDeep Learning with PyTorch: https://aka.ms/AIShow/PyTorchEnterprise/FreeCreate a Free account (Azure) https://aka.ms/aishow-seth-azurefreeGet Started with Machine Learning https://aka.ms/AIShow/StartMLAI Show https://aka.ms/AIShowAI for Developers https://aka.ms/AIShow/AIforDevelopersAzure Machine Learning https://aka.ms/AIShow/AzureML Follow Seth https://twitter.com/sethjuarezFollow Alon https://linkedin.com/in/alonbochmanDon't miss new episodes, subscribe to the AI Show https://aka.ms/AIShowsubscribeJoin us every other Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive

On this week's episode, Ashly Yeo will demo the exciting announcement made at #MSBuild about What's new in Text Analytics for Health!Jump to:[00:15] Seth welcomes Ashly[01:02] #MSBuild announcements on Text Analytics for Health[02:48] How to access Text Analytics for Health[03:40] API Output visualization 05:38 Demo in Visual Studio Code[08:54] Demo in Python SDK - see sample link belowLearn more:How-to Text Analytics for health https://aka.ms/AIShow/TextAnalyticsforHealth/HowToText Analytics for health sample https://aka.ms/AIShow/TextAnalytics/SampleText Analytics Tech Community blog https://aka.ms/AIShow/TechCommunity/TextAnalyticsAI Show https://aka.ms/AIShowCreate a Free account (Azure) https://aka.ms/aishow-seth-azurefreeGet Started with Machine Learning https://aka.ms/AIShow/StartMLAI for Developers https://aka.ms/AIShow/AIforDevelopersAzure Machine Learning https://aka.ms/AIShow/AzureMLFollow Seth https://twitter.com/sethjuarezDon't miss new episodes, subscribe to the AI Show https://aka.ms/AIShowsubscribeJoin us every other Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive

On this week's episode, Jeff Mendenhall is here to demo the exciting announcement made at #MSBuild - Reducing time to value with Azure Applied AI Services.Jump to:[00:00] AI Show begins[00:16] Seth welcomes Jeff[00:58] Why Azure Applied AI Services?[03:01] From general purpose to scenario-specific[04:34] Azure Video Analyzer[06:05] Azure Metrics Advisor[07:15] Who is using Azure Applied AI Services?[08:34] Azure Applied AI Services in a nutshellLearn more:Azure Applied AI Services: https://aka.ms/AIShow/AppliedAIServicesApplied AI Services doc: https://aka.ms/AIShow/AppliedAIDocCreate a Free account (Azure) https://aka.ms/aishow-seth-azurefreeGet Started with Machine Learning https://aka.ms/AIShow/StartMLAI for Developers https://aka.ms/AIShow/AIforDevelopersAzure Machine Learning https://aka.ms/AIShow/AzureMLFollow Seth https://twitter.com/sethjuarezFollow Jeff https://twitter.com/JeffLMendenhallDon't miss new episodes, subscribe to the AI Show https://aka.ms/AIShowsubscribeJoin us every other Friday, for an AI Show livestream on Learn TV https://aka.ms/LearnTV and YouTube https://aka.ms/AIShowLive

Computer Vision just updated its models with industry-leading models built by Microsoft Research. These models are tagging contents in an image with significantly more detail & accuracy, across more languages. Jump to:[00:16] Seth welcomes Sanjeev[00:48] What is OCR?[02:21] What's new to OCR? Multiple languages in same text line, handwritten and print, confidence thresholds and large documents![03:55] How Read operations works[05:14] Demo - Read image as text[07:05] Demo - Handwritten classification[09:21] Demo - Mixed languages in same text selected pages extraction[12:10] Seventy three languages supported by Read[13:25] Demo - Text lines in Reading order[15:49] Demo - OCR Applied (Form Recognizer) layouts and tablesLearn more:What is Optical character recognition? https://aka.ms/AIShow/OpticalDocQuickstart: Read client library or REST API https://aka.ms/AIShow/RESTAPIQuickstartHow to call the Read API https://aka.ms/AIShow/ReadAPIDocInstall Read OCR Docker containers from Computer Vision https://aka.ms/AIShow/OCRDockerDocCreate a Free account (Azure) https://aka.ms/aishow-seth-azurefreeGet Started with Machine Learning https://aka.ms/AIShow/StartMLAI for Developers https://aka.ms/AIShow/AIforDevelopersAzure Machine Learning https://aka.ms/AIShow/AzureMLFollow Seth https://twitter.com/sethjuarezFollow Sanjeev https://twitter.com/SanjeevJagtapDon't miss new episodes, subscribe to the AI Show https://aka.ms/AIShowsubscribeJoin us every other Friday, for an AI Show livestream on Learn TV https://aka.ms/LearnTV and YouTube https://aka.ms/AIShowLive

On this week's episode of the AI Show Live with Seth Juarez, Tony Xing joins the show to talk about the latest multivariate capabilities with Anomaly Detector. Stay tuned after the segment as Seth gets back to work on his Roshambo game.Jump to:[00:17] Seth welcomes Tony[00:49] What is Anomaly Detector?[01:30] New to Anomaly Detector: Multivariate detection[02:55] Use case scenario visualization[05:00] API Endpoints[08:57] Submit the model training with a blob file[13:44] How does the data come back?[14:11] Who is using?Learn more:Anomaly Detector Multivariate blog: https://aka.ms/ADMultivariateBlogAnomaly Detector Multivariate quickStarts https://aka.ms/ADMultivariateQuickstartsAnomaly Detector best practices https://aka.ms/ADBestPracticesBuild predictive maintenance solution https://aka.ms/ADBuildPMSolutionAzure Anomaly Detector sample notebook: https://aka.ms/ADSampleNotebookJoin the Roshambo Discussion: https://aka.ms/AIShow/RoshamboDiscussionAI Show https://aka.ms/AIShowCreate a Free account (Azure) https://aka.ms/aishow-seth-azurefreeGet Started with Machine Learning https://aka.ms/AIShow/StartMLAI for Developers - https://aka.ms/AIShow/AIforDevelopersAzure Machine Learning https://aka.ms/AIShow/AzureMLFollow Seth https://twitter.com/sethjuarezFollow Tony https://twitter.com/XingGuodongDon't miss new episodes, subscribe to the AI Show https://aka.ms/AIShowsubscribeJoin us every other Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive

In this episode of the AI Show Seth, Gary Pretty and Vishesh Oberoi showcase how Azure Bot Service's new telephony channel and Bot Framework Composer's recent enhancements complement each other.Jump to:[00:00] Welcome[01:01] What is Azure Bot Service?[02:10] What's new in Azure Bot Service? Telephony Channel[03:46] How Telephony Channel is used[07:02] Telephony Channel Demo[11:25] Where to go to learn more: https://aka.ms/AIShow/TelephonyDoc[12:05] What is Bot Framework Composer?[12:52] Bot Framework Composer Demo[21:38] How to use Package Manager[23:07] Seth calls the Bot[25:25] Barge-in or Allow Interrupt[28:31] Learn moreLearn more:Join conversational AI Ask Microsoft Anything https://aka.ms/AIShow/AzureAIAMA​Telephony Documentation https://aka.ms/AIShow/TelephonyDoc​Azure Bot Services https://aka.ms/AIShow/AzureBotServices​TechCommunity blog https://aka.ms/AIShow/BotFrameworkblog​DevBot Framework https://aka.ms/AIShow/Composer​AI Show https://aka.ms/AIShow​Create a Free account (Azure) https://aka.ms/aishow-seth-azurefree​Get Started with Machine Learning https://aka.ms/AIShow/StartML​AI for Developers https://aka.ms/AIShow/AIforDevelopers​Azure Machine Learning https://aka.ms/AIShow/AzureML​Follow Seth https://twitter.com/sethjuarez​Follow Gary https://twitter.com/GaryPretty​Follow Vishesh https://twitter.com/ovisheshDon't miss new episodes, subscribe to the AI Show https://aka.ms/AIShowsubscribe​Join us every Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV​ - https://aka.ms/AIShowLive

Leveraging Kubernetes ​and Azure Arc to train ML Models ​across hybrid cloud. In this episode Seth talks with Saurya Das about this new Azure Machine Learning integration with Azure Arc – to enable Data Scientists to use existing kubernetes infrastructure on-premises or in multicloud to run machine learning. Jump to:[00:48] What is Machine Learning?[01:28] Run Azure Machine Learning anywhere[02:37] What is Azure Arc?[03:24] Demo: Use on premises Azure Machine Learning clusters using Azure Arc Learn more:Azure Machine Learning Blog - https://aka.ms/AIShow/AzureMLBlogAzure Arc Blog - https://aka.ms/AIShow/AzureArcBlog AI Show https://aka.ms/AIShowCreate a Free account (Azure) https://aka.ms/aishow-seth-azurefreeGet Started with Machine Learning https://aka.ms/AIShow/StartMLAI for Developers https://aka.ms/AIShow/AIforDevelopersAzure Machine Learning https://aka.ms/AIShow/AzureML Follow Seth https://twitter.com/sethjuarezDon't miss new episodes, subscribe to the AI Show https://aka.ms/aishowsubscribe Join us every other Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive

Documents contain invaluable information powering core business processes. Extracting information from these documents with minimum manual intervention helps bolster organizational efficiency and productivity. As more and more processes and workflows get automated, the need for new features to help extract text and structures increases. The new capabilities in Form Recognizer which were announced at Ignite support pre-built IDs, invoices and 73 new languages. Jump to:[01:00] What's new in Form Recognizer[01:40] Get Started[02:42] Demo[14:49] How to customize Form Recognizer Learn more:What's New in Form Recognizer https://aka.ms/AIShow/FormRecognizer/WhatsNewTech community blog https://aka.ms/AIShow/FormRecognizerBlogDocumentation https://aka.ms/AIShow/FormRecognizerDocGet started https://aka.ms/AIShow/FormRecognizer/GetStarted AI Show https://aka.ms/AIShowCreate a Free account (Azure) https://aka.ms/aishow-seth-azurefreeGet Started with Machine Learning https://aka.ms/AIShow/StartMLAI for Developers - https://aka.ms/AIShow/AIforDevelopersAzure Machine Learning https://aka.ms/AIShow/AzureML Follow Seth https://twitter.com/sethjuarezDon't miss new episodes, subscribe to the AI Show https://aka.ms/aishowsubscribe Join us every other Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive

Walkthrough of newly released PyTorch Learn the basics tutorial with PyTorch Developer Advocate Suraj Subramanian.Jump to:[00:38] What is PyTorch[01:09] Why is PyTorch a Good Library to Start With[02:17] Learn the BasicsLearn more:Learn the basics - https://aka.ms/PyTorch/LearntheBasicsPyTorch.org - https://pytorch.org/PyTorch on YouTube - https://www.youtube.com/pytorchCreate a free account (Azure) https://aka.ms/aishow-seth-azurefree​Don't miss new episodes, subscribe to the AI Show - https://aka.ms/aishowsubscribe​Follow Seth https://twitter.com/sethjuarez Follow Suraj https://twitter.com/subramen Join us every other Friday for an AI Show livestream on Learn TV https://aka.ms/LearnTV​ and YouTube https://aka.ms/AIShowLive

The new semantic search capability in Azure Cognitive Search uses Bing AI models to help you find the most relevant information. This will be a discussion on how you can enable your enterprise and customers to find the right information quickly by using an engine that understands the meaning of words, not just syntax/lexical analysis.We'll explain how the system works, answer your questions, demo the capability and discuss its value. While we will use state of the art deep learning models, no prior machine learning background is required.Jump to:[01:00] What is Azure cognitive search[02:58] What's new in semantic search[09:36] Leveraging Bing's state of the art deep neural networks through Azure[11:01] Demo[18:34] How to enable this for your serviceLearn more:Semantic Search Documentation https://aka.ms/semanticsearchdocsSemantic Search Preview (form) http://aka.ms/semanticpreviewACOM page https://aka.ms/AIShow/SearchAzure Blog https://aka.ms/AIShow/ApplyAIBlogSemantic Search Blog: https://aka.ms/AIShow/SemanticSearchBlogAzure Cognitive Search AMA Mar 10 9am pacific: https://aka.ms/AzureCognitiveSearchAMA Create a Free account (Azure) https://aka.ms/aishow-seth-azurefreeDeep Learning vs. Machine Learning https://aka.ms/AIShow/DLvMLGet Started with Machine Learning https://aka.ms/AIShow/StartMLFollow Seth https://twitter.com/sethjuarezDon't miss new episodes, subscribe to the AI Show join us every other Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive

Error Analysis, a new Responsible AI open source toolkit, enables machine learning practitioners to identify model errors and diagnose the root causes behind these errors, helping to build responsible, reliable, and trusted solutions.Jump to: [01:24] About AI models[02:37] Error analysis [04:23] Interpretability and fairness [06:34] About Error Analysis toolkit [11:46] Error explorer demo [22:18] Debugging demos - Global and Local explanationsLearn more: Blog on MSFT Tech Community: https://aka.ms/AIShow/RAIBlog Website: https://aka.ms/AIShow/RAISiteReadme: https://aka.ms/AIShow/EADSample notebook: https://aka.ms/AIShow/Notebooks/EACreate a Free account (Azure)Don't miss new episodes, subscribe to the AI Show join us every other Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive

Learn about the latest research breakthrough in Image captioning and latest updates in Azure Computer Vision 3.0 API. Image captioning service generates automatic captions for images, enabling developers to use this capability to improve accessibility in their own applications and services. Jump to: [00:47] What is computer vision cognitive services? [01:15] What is Imaging Captioning? [02:40] Novel Object Captioning at scale[06:25] Image captioning examples [08:25] Demo: API can be integrated into your application [11:15] What's new in Computer Vision API [12:38] Get started For more information:What's that? Microsoft's latest breakthrough, now in Azure AI, describes images as well as people do - The AI BlogImage Descriptions - Computer Vision - Azure Cognitive Services | Microsoft DocsNovel object captioning surpasses human performance on benchmarks - Microsoft ResearchCreate a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine LearningDon't miss new episodes, subscribe to the AI Show and join us every other Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive

In this episode of the AI Show, Seth, Edward and Sarah talk about a recently GA'd feature called Custom Neural Voice.Jump to:[04:05] About Traditional TTS and Neural TTS[05:20] Neural Voices samples[06:10] About Custom Neural Voice (now in GA)[08:30] Customer examples[10:37] responsible AI considerationsLearn more:Text-to-speech documentation https://aka.ms/AIShow/SpeechDocs​Build a natural custom voice for your brand blog https://aka.ms/AIShow/CNVblog​Apply for access to Custom Neural Voice https://aka.ms/AIShow/ApplyRead through the questions from the Feb 10 'Ask Microsoft Anything event' https://aka.ms/AzureAIAMAStart your 30 day learning journey today https:///aka.ms/AIShow/LearnCreate a Free account (Azure)Don't miss new episodes, subscribe to the AI Show join us every other Friday, for an AI Show livestream on Learn TV and YouTube https://aka.ms/LearnTV - https://aka.ms/AIShowLive

We are introducing a new feature to our Translator Cognitive Service that will delight and excite developers! With this new feature, developers can intelligently translate documents (supporting a variety of file types) in batch. Jump To:[00:55] Overview[02:34] Sample Use Cases[03:23] Introduction to document translation[04:18] Demo[07:56] Output from document translationFor More Information:Translator DocumentationTranslator Home PageTranslator | Microsoft AzureCreate a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine LearningDon't miss new episodes, subscribe to the AI Show

Machine learning is an important piece of any Analytics solution. The integration between Synapse and Azure ML promotes a seamless collaboration between data professionals in Synapse and ML professionals in Azure ML. In Synapse Studio, users of all skill levels can leverage ML models built in Azure Machine Learning across their organizations to analyze and enrich data. ​Synapse users can also leverage code free and code experiences to seamlessly train ML models using in Synapse notebooks thanks to automated machine learning powered by Azure Machine Learning. ​The integration between Synapse and Azure ML is making data enrichment through machine learning more accessible to Synapse users, which allows for greater analytics insights. Jump To:[00:46] – What is Azure Synapse?[07:08] – Overview of new ML experiences[11:30] – Demo: Leverage Azure Cognitive Services in Azure Synapse[15:21] – Demo: Train a model with AutoML in Azure Synapse[18:06] – Demo: Model scoring in Azure Synapse dedicated SQL PoolFor more information:Getting Started ToolkitAzure Synapse Automated ML TutorialLink an Azure Synapse WS to Azure ML WSMachine Learning in SynapseScoring TutorialCreate a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine LearningDon't miss new episodes, subscribe to the AI Show

Andreas Vrålstad chats with Seth Juarez about how we can use deep learning for audio. We'll explain how we can use sounds, convert them into images and build a classifier model to tag songs according to mood.Jump To:[00:00] Introduction[01:05] Introducing the case[01:16] Demo[02:42] Working with the Peltarion Platform[17:05] Building a spectrogram[22:57] Calling the deployed modelLearn More: Do this yourself - step-by-step tutorialHow this case has been done in real life. Case story with the music marketplace, Epidemic SoundCreate a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine LearningDon't miss new episodes, subscribe to the AI Show

In today's AI show, you will learn about the recently launched Opinion Mining and Async offerings of Text Analytics. In the first half, we will discuss how Opinion Mining (an extension of Sentiment Analysis) helps explore customers' perception of aspects/opinions, such as specific attributes of products or services, in text. In the second half, we will learn about the new Async capabilities of Text Analytics, which will allow bundling various skills of Text Analytics and also allows large amount of text up to 125K characters to be sent to Text Analytics via /analyze endpoint.Jump To:[00:55] - Introduction to Cognitive Services[01:50] - Introduction to Text Analytics[02:51] - Introduction to Opinion Mining[04:39] - Introduction to Async API (/analyze)[06:43] - Demo of Opinion Mining[11:30] - Demo of Async API (/analyze)[14:19] - Common scenarios of using Text Analytics[16:57] - Getting started with Text Analytics More Information:QuickStart Use the Text AnalyticsSentiment analysis and Opinion MiningGettingStarted with Text AnalyticsCreate a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine LearningDon't miss new episodes, subscribe to the AI Show

Text Analytics for health is a preview feature of Text Analytics which enables developers to process and extract insights from unstructured clinical and biomedical text. Through a single API call, using NLP techniques such as named entity recognition, entity linking, relation extraction and entity negation, Text Analytics can extract critical and relevant medical information without the need for time-intensive, manual development of custom models. We will demonstrate how to make API calls to the synchronous operation offered in a downloadable container and also to the asynchronous operation offered in the hosted web API.Jump To:[01:49] About Text Analytics[04:20] Demo Text Analytics for Health[08:27] Demo API in postman[12:51] Data privacy[14:14] Find moreMore Information:Text Analytics for Health - BlogText Analytics for Health - Documentation Create a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine LearningDon't miss new episodes, subscribe to the AI Show

Being able to explain your own code a few months after you wrote it is hard. Imagine having to explain the decisions of some AI algorithm a few years after it run! However, it is relatively easy to set up your development workflow to make that possible, as long as you realize that the way we build ML and AI is fundamentally different from traditional software engineering. In a nutshell, it is all about: reproducible research, development and deployment. It is made possible by a clever use of modern notebook environments, including Azure ML Compute Instances, as opposed to the more traditional IDEs, like Visual Studio Code. Rafal Lukawiecki has been actively working in data science, machine learning, and data mining for well over a decade, and he has formally studied and used artificial intelligence long before it was popular, back in the '90s. Watch this episode to find out how he organizes his reproducible workflow.Jump To:[02:30] Learn reproducible research with Rafal Lukawiecki[03:01] Modelling and exploration vs software development[09:28] Steps to a reproducible workflow[15:20] Demo: Workflow using RStudio and RMarkdown running locally[22:25] Demo: RMarkdown notebooks in an Azure ML Compute InstanceMore Information:Learn more about this way of using R with RafalVideos available at TecflixFollow Rafal on LinkedInCreate a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine LearningDon't miss new episodes, subscribe to the AI Show

The next version of QnA Maker advances several core capabilities like better relevance and precise answering, by introducing state-of-art deep learning technologies. In addition, it also simplifies resource management by reducing the number of resources deployed. The latest version will enable customers with strict geo requirements to deploy the service in the region of their choice end-to-end.Jump To:[04:20]More Information:What's new in QnA MakerManage QnA Maker ResourcesMigrate a knowledge base using export-importCreate a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine LearningDon't miss new episodes, subscribe to the AI Show

In this episode we will talk about the Python community and the scientific Python ecosystem. So if you always wanted to know what is so great about Python for Machine learning and its community this episode is for you.More Information: Python and TensorflowWhat is DVCRun Jupyter NotebooksCreate a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine LearningDon't miss new episodes, subscribe to the AI Show

PyTorch is one of the most popular open source machine learning framework that accelerates the path from research to production deployment. In this tutorial, Dmytro Dzhulgakov, core contributor for PyTorch, will go through an introductory level hands-on tutorial for building fashion recognizer. Jump To: [01:17] PyTorch Core functionality introduction[05:08] Demo: classification problem[10:38] Demo: Define network architecture[13:13] Demo: Define loss function & optimizer[16:04] Demo: Setting up TensorBoard[16:45] Demo: Training LoopMore Information: PyTorch Tutorials TorchVisionPyTorch GitHubTensorboardCreate a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine LearningDon't miss new episodes, subscribe to the AI Show

Learn the basics of PyTorch such as what it is, how to build and deploy a model, its strong community and more. Jump To: [01:15] What makes PyTorch different from other frameworks?[02:31] What is PyTorch?[05:35] How does PyTorch deal with data?[10:35] Building a model with PyTorch[22:08] Deploying PyTorch models to production[29:09] PyTorch community and ecosystemLearn More: PyTorch TutorialsStart Local with PyTorchCreate a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine LearningDon't miss new episodes, subscribe to the AI Show

ONNX Runtime is a high-performance inferencing and training engine for machine learning models. This show focuses on ONNX Runtime for model inference. ONNX Runtime has been widely adopted by a variety of Microsoft products including Bing, Office 365 and Azure Cognitive Services, achieving an average of 2.9x inference speedup. Now we are glad to introduce ONNX Runtime quantization and ONNX Runtime mobile for further accelerating model inference with even smaller model size and runtime size. ONNX Runtime keeps evolving not only for cloud-based inference but also for on-device inference.Jump To: [01:02] ONNX and ONNX Runtime overview[02:26] model operationalization with ONNX Runtime[04:04] ONNX Runtime adoption[05:07] ONNX Runtime INT8 quantization for model size reduction and inference speedup[09:46] Demo of ONNX Runtime INT8 quantization[16:00] ONNX Runtime mobile for runtime size reductionLearn More: ONNX RuntimeFaster and smaller quantized NLP with Hugging Face and ONNX RuntimeONNX Runtime for Mobile PlatformsONNX Runtime Inference on Azure Machine Learning Create a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine LearningDon't miss new episodes, subscribe to the AI Show

Dictation in productivity apps such as Word empower people to conquer the blank page. Dictating is a fast and easy way to get your thoughts on the page during brainstorming, outlining, and authoring content. Office voice commanding is the next step to make dictation more powerful. Using AI powered by Microsoft Cognitive Services, Microsoft 365 users save time and effort with transcription and voice commanding. Office voice commanding is powered by Microsoft Cognitive services, including Cognitive Speech Studio and Language Understanding Cognitive Service.Learn More: More about voice commands on the Microsoft 365 BlogDictate your documents in Word Help ArticleLanguage Understanding (LUIS)Create a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine LearningDon't miss new episodes, subscribe to the AI Show

When you think of "deep learning" you might think of teams of PhDs with petabytes of data and racks of supercomputers. But it turns out that a year of coding, high school math, a free GPU service, and a few dozen images is enough to create world-class models. fast.ai has made it their mission to make deep learning as accessible as possible, and in this interview fast.ai co-founder Jeremy Howard explains how to use their free software and courses to become an effective deep learning practitioner.Learn More:Welcome to FastAiPractice Deep Learning FastAiCreate a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine LearningDon't miss new episodes, subscribe to the AI Show

We discuss reinforcement learning – an AI approach that is especially promising for training naturally behaving game characters with nuanced reactions to human players. Viewers learn about key concepts of reinforcement learning in the context of Project Malmo – which enables RL research in the game Minecraft, and Project Paidia – which aims specifically at creating game agents that learn to genuinely collaborate with human players.Jump To: [00:50] What is reinforcement learning [02:26] Project Malmo – Minecraft as a platform for AI research[05:00] Project Paidia: towards RL agents that learn to collaborate with human players[09:00] Project Paidia demo[11:00] Call to action -AI Innovation page (Project Paidia) + Azure ML notebooks Learn More: Project Paidia deep dive pageAzure notebooks – try this todayGame Intelligence researchCreate a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine LearningDon't miss new episodes, subscribe to the AI Show

In this video, you will see how you can use drag-and-drop Designer to build, test and deploy a production-ready image classification model with state-of-the-art algorithms.Jump To: [01:19] Demo StartLearn More: Designer OverviewDesigner TutorialDesigner SamplesCreate a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine LearningDon't miss new episodes, subscribe to the AI Show

In this video, you will see what Automated Machine Learning is and how you can use it to solve machine learning problems. We also go through a demo to solve a banking problem starting from a dataset to deploying models to production, all without a single line of code.Jump To:[00:50] What is automated Machine learning[02:09] how does it work? A demo[13:30] the part that floored Seth[14:37] model explanation magicLearn More:What is automated machine learning Prevent overfitting and imbalanced data with automated machine learningCreate a classification model with automated ML in Azure Machine LearningForecast demand with automated machine learningCreate a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine LearningDon't miss new episodes, subscribe to the AI Show

We're introducing to you the preview of Metrics Advisor, a new Cognitive Service, an AI analytics service that proactively monitors metrics and diagnoses issues.Learn More: Metrics Advisor & Anomaly Detector Advisors Teams groupMetrics AdvisorMetrics Advisor DocsCreate a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine LearningDon't miss new episodes, subscribe to the AI Show

Computer Vision is an Azure Cognitive Service which runs vision AI on images, and is a new feature of the Computer Vision service. It runs Vision AI on live and recorded video streams to understand people's movement in physical spaces. Learn More:Computer Vision DocNew to Cognitive ServicesCreate a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine LearningDon't miss new episodes, subscribe to the AI Show

Join Seth Juarez as he delves into ethical concerns with AI with Josh Lovejoy, who leads Design for Microsoft Ethics & Society within Cloud + AI, and Sarah Bird, who leads Responsible AI for Cognitive Services. This episode explores how to think about Ethical AI and how to ensure the software you build is designed, developed and deployed ethically. Josh and Sarah describe how Ethics & Society works closely with product teams to make human-centered AI / ML technologies that serve people by appreciating the constraints and measuring accuracy and inaccuracy throughout the product development lifecycle.Learn More:Responsible AI Resources Responsible Innovation Responsible Innovation: A Best Practices ToolkitMicrosoft Responsible Machine LearningCreate a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine LearningDon't miss new episodes, subscribe to the AI Show

Learn how Azure ML supports Open Source ML Frameworks and MLflow in AzureML. We'll walk through a ScikitLearn and Pytorch example to show the built in support for ML frameworks. We'll also go over how you can take these examples and easily track your artifacts with MLflow.Learn More: Azure ML ExamplesAzure ML Curated EnvironmentsTrack and Monitor ML Flow Create a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine Learning Don't miss new episodes, subscribe to the AI Show

Andreas Müller chats with Seth Juarez about his journey, watch for a short overview of scikit-learn and introduce his new dabl project. Stay tuned till the end to find out what he thinks is next for ML. Jump To: [20:20] Scki-learn demo start[25:20] Dabl demo startMore Information: DABLScikit Learn Create a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine Learning Don't miss new episodes, subscribe to the AI Show

Learn about the latest updates in Azure Form Recognizer, including the Form Recognizer v2.1 Preview! Form Recognizer is a Cognitive Service that lets you identify and extract text, key/value pairs, and table data from documents. With Form Recognizer you can train custom models to extract structured data from your forms and documents.Learn More: DocsQuickstart for the demo we did todayGitHub for Form ToolsCreate a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine Learning Don't miss new episodes, subscribe to the AI Show

The Azure Cognitive Services Face service provides algorithms that detect, recognize, and analyze human faces in images. The ability to process human face information is important in many different software scenarios. In this episode we walk you through the latest innovation in Face API. Learn More: Face RecognitionFace DocsCreate a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine Learning Don't miss new episodes, subscribe to the AI Show

We’ll talk about our latest progress on Text to Speech, and how you could use it to enable your apps to speak naturally.More Information: CS Text To SpeechText To Speech DocSpeech StudioCreate a Free account (Azure)Deep Learning vs. Machine Learning Get Started with Machine Learning Don't miss new episodes, subscribe to the AI Show

Trove is a new marketplace from Microsoft connecting AI/ML developers who can crowdsource licensed, high-quality data (photos) for training their Computer Vision AI projects from photo takers. We talk about the principles, ideas and mission behind Trove and share a demo on how Trove helps photo takers sell high quality photos for ML projects with transparency & privacy. Jump To:[02:20] Principles, ideas and mission behind Trove[07:13] Demo[12:29] Closing & Call to action Learn More: Try TroveTrove Garage ProfileCreate a Free account (Azure) Deep Learning vs. Machine Learning Get Started with Machine Learning Don't miss new episodes, subscribe to the AI Show

Parallel run in Azure Machine Learning enables big data processing in distributed manner. In this episode, you will find out more about Azure Machine Learning dataset; how it can help manage your data in machine learning workflow; and how to use dataset in parallel run to accelerate your big data processing. [02:00] Demo StartLearn More: Azure Machine Learning Datasets Parallel Run Sample NotebookCreate a Free account (Azure) Deep Learning vs. Machine Learning Get Started with Machine Learning Don't miss new episodes, subscribe to the AI Show