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Introduction to Bots
This video segement teaches you the basics of bots.
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Creating a Bot in Azure Portal
This video segment walks you through creating a bot in Azure Portal.
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Training a custom ML model with Model Builder
This video segment teaches you how to train a custom ML model with Model Builder.
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Testing your bot
This video segment shows you how to test your bot.
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Summary
This segment summarizes what is learned in this video.
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Capabilities of ML.NET and Model Builder
This video segement introduces ML.NET, Microsoft’s open source machine learning framework and Model Builder, its visual interface to build, train, and deploy custom machine learning models.
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Getting a dataset for a custom ML model training
This video segment teaches you how to get a dataset for a custom ML model training.
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Connecting the model to the bot using ML.NET
This video segment teaches you how to connect the model to the bot using ML.NET, Microsoft’s open source machine learning framework.
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What’s next?
This video segment mentions other resources for learning about chatbots and ML.NET.
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A Quick Solution - MLaaS
This video introduces you to the recent innovation in the field of data science and that is ML as a Service, followed by a quick introduction to the instructor and how he is perfectly poised to deliver this co...
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Do It Yourself
This video tells you how your approach of classical ML development depends on your data size and type.
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Centroid-based Clustering
In this video, you will learn centroid-based clustering. The K-means, K-medoids, K-medians, and K-means++ algorithms fall under this category.
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Less Efforts with ANN
This video describes fully what all you need in building your own ANN network.
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Distribution-based Clustering
This video covers the distribution-based clustering, which is based on the statistical distribution models. Objects belonging to the same distribution form a cluster. This type of distribution is good at captu...
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Clustering
This video will show you why clustering is the most daunting task for a data scientist and provides guidelines on how to cluster small to enormously sized datasets, with the help of an organized list of severa...
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Clustering Huge Datasets
This video teaches how to cluster enormous sized datasets. You need to use the divide-n-conquer strategy. BIRCH and CLARANS are the two popular algorithms used for clustering huge datasets.
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Affinity Propagation Clustering
This video describes altogether different type of clustering. Here, the clusters are formed through peer messaging. You do not have to prior estimate the number of clusters. The groups are created by matching ...
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Introduction and background
In this segment, we will introduce the problem definition of transfer learning, especially the problem formulation, its notations. Most importantly, we introduce the necessity of transfer learning in different...
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Feature-based transfer learning
In this segment, feature-based transfer learning approaches are introduced. Specifically, we introduce two main categories: explict distance and implicit distance, where the first one utilizes existing distanc...
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Datasets, benchmarks, and evaluations
In this video, we will introduce the popular benchmarks and datasets in the transfer learning research area, as well as the evaluation protocols.