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 courseSpecify cases in which it's advantageous to use cntk over other platformsDescribe how to load and use external data using microsoft cntkOutline the cntk training process when called with an imperative apiOutline the cntk training process when called with a declarative apiDefine epochs and batch sizes in cntk and specify how to choose the optimal values for best performanceRecognize the model serialization process using cntkIdentify how cntk can be used for model visualization
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Use cntk to create and train a feedforward neural network and demonstrate its performanceWork with cntk evaluation tools to evaluate previously created cntk machine learning modelsUse 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 modelsUse 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 modelsUtilize 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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2m 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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2m 29sIn this video, find out how to outline the CNTK training process when called with an imperative API. FREE ACCESS
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2m 45sIn this video, you will outline the CNTK training process when using the declarative API. FREE ACCESS
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3m 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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2m 59sAfter completing this video, you will be able to recognize the model serialization process using CNTK. FREE ACCESS
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3m 35sIn this video, you will learn how to use CNTK for model visualization. FREE ACCESS
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3m 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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3m 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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3m 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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3m 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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4m 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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3m 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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56sIn this video, we will summarize the key concepts covered in this course. FREE ACCESS
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