Advanced Functionality of Microsoft Cognitive Toolkit (CNTK)
Microsoft Cognitive Toolkit (CNTK)
| Expert
- 15 videos | 47m 10s
- Includes Assessment
- Earns a Badge
Microsoft Cognitive Toolkit provides powerful machine learning and deep learning algorithms for developing AI. Knowing which problems are easier to solve using Microsoft CNTK over other frameworks helps AI practitioners decide on the best software stack for a given application. In this course, you'll explore advanced techniques for working with Microsoft CNTK and identify which cases benefit most from MS CNTK. You'll examine how to load and use external data using CNTK and how to use its imperative and declarative APIs. You'll recognize how to carry out common AI development tasks using CNTK, such as working with epochs and batch sizes, model serialization, model visualization, feedforward neural networks, and machine learning model evaluation. Finally, you'll implement a series of practical AI projects using Python and MS CNTK.
WHAT YOU WILL LEARN
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discover the key concepts covered in this course
specify cases in which it's advantageous to use CNTK over other platforms
describe how to load and use external data using Microsoft CNTK
outline the CNTK training process when called with an imperative API
outline the CNTK training process when called with a declarative API
define epochs and batch sizes in CNTK and specify how to choose the optimal values for best performance
recognize the model serialization process using CNTK
identify how CNTK can be used for model visualization -
use CNTK to create and train a feedforward neural network and demonstrate its performance
work with CNTK evaluation tools to evaluate previously created CNTK machine learning models
use Python to apply pre-processing techniques to diabetic patients' data and use this data to troubleshoot the creation and training of CNTK machine learning classification models
use Python to apply pre-processing techniques to credit rating data and use this data to troubleshoot the creation and training of CNTK machine learning regression models
utilize Python to apply pre-processing techniques to housing price data and use this data to troubleshoot the creation and training of CNTK machine learning regression models
" utilize Python to apply pre-processing techniques to professional salary data and use this data to troubleshoot the creation and training of CNTK machine learning classification models "
summarize the key concepts covered in this course
IN THIS COURSE
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2m 26s
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4mAfter completing this video, you will be able to specify cases in which it is advantageous to use CNTK over other platforms. FREE ACCESS
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3. Working With Data in CNTK2m 38sAfter completing this video, you will be able to describe how to load and use external data using Microsoft's CNTK. FREE ACCESS
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4. CNTK Training Using Imperative APIs2m 29sIn this video, find out how to outline the CNTK training process when called with an imperative API. FREE ACCESS
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5. CNTK Training Using Declarative APIs2m 45sIn this video, you will outline the CNTK training process when using the declarative API. FREE ACCESS
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6. Epochs and Batch Sizes in CNTK3m 47sIn this video, you will learn how to define epochs and batch sizes in CNTK, and how to choose optimal values for best performance. FREE ACCESS
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7. Model Serialization Using CNTK2m 59sAfter completing this video, you will be able to recognize the model serialization process using CNTK. FREE ACCESS
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8. Model Visualization Using CNTK3m 35sIn this video, you will learn how to use CNTK for model visualization. FREE ACCESS
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9. CNTK Model Training3m 8sIn this video, you will learn how to use CNTK to create and train a feedforward neural network and how to evaluate its performance. FREE ACCESS
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10. CNTK Model Evaluation3m 8sDuring this video, you will learn how to use CNTK evaluation tools to evaluate previously created CNTK machine learning models. FREE ACCESS
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11. Diabetes Prediction Using CNTK3m 31sFind out how to use Python to apply pre-processing techniques to data from diabetic patients and use this data to troubleshoot the creation and training of CNTK machine learning classification models. FREE ACCESS
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12. Credit Rating Prediction Using CNTK3m 45sIn this video, you will learn how to use Python to apply pre-processing techniques to credit rating data and use this data to troubleshoot the creation and training of CNTK machine learning regression models. FREE ACCESS
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13. Housing Price Prediction Using CNTK4m 11sFind out how to use Python to apply pre-processing techniques to housing price data and use this data to troubleshoot the creation and training of CNTK machine learning regression models. FREE ACCESS
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14. Salary Prediction Using CNTK3m 53sIn this video, you will learn how to use Python to apply pre-processing techniques to professional salary data and use this data to troubleshoot the creation and training of CNTK machine learning classification models. FREE ACCESS
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15. Course Summary56sIn this video, we will summarize the key concepts covered in this course. FREE ACCESS
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