Machine Learning & Deep Learning Tools in the Cloud

Machine Learning    |    Intermediate
  • 9 videos | 22m 9s
  • Includes Assessment
  • Earns a Badge
Rating 4.0 of 40 users Rating 4.0 of 40 users (40)
This Skillsoft Aspire course explores the machine learning solutions provided by AWS (Amazon Web Services) and Microsoft, and how to compare the tools and frameworks that can be used to implement machine learning, and deep learning. You will learn to become efficient in data wrangling by building a foundation with data tools and technology. This course explores Machine Learning Toolkit provided by Microsoft, which provides various algorithms and applies artificial intelligence and deep learning. Learners will also examine Distributed Machine Learning Toolkit, which is hosted on Azure. Next, explore the machine learning tools provided by AWS, including DeepRacer and DeepLens which provide deep learning capabilities. You will learn how to use Amazon SageMaker, and how Jupyter notebooks are used to test machine learning algorithms. You will learn about other AWS tools, including TensorFlow, Apache MXNet, and Deep Learning AMI. Finally, learn about different tools for data mining and analytics, and how to build and process a data pipeline provided by KNIME (Konstanz Information Miner).

WHAT YOU WILL LEARN

  • Recognize the capabilities of microsoft machine learning tools
    Recognize the machine learning tools provided by aws for data analysis
    Specify spark's machine leaning capabilities and the features of pyspark
    List frameworks that can be used to implement deep learning such as keras, tensorflow, caffe, and pytorch
  • Implement deep learning using keras
    List tools that can be used to implement data mining and analytics and their features
    Demonstrate the capabilities of building and processing data pipeline with knime
    Set up keras, implement a deep learning algorithm, and build data pipelines using knime

IN THIS COURSE

  • 1m 21s
  • 3m 8s
    Upon completion of this video, you will be able to recognize the capabilities of Microsoft machine learning tools. FREE ACCESS
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    3.  AWS and Machine Learning
    2m 30s
    Upon completion of this video, you will be able to recognize the machine learning tools provided by AWS for data analysis. FREE ACCESS
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    4.  Spark Machine Learning Capabilities
    2m 15s
    After completing this video, you will be able to specify Spark's machine learning capabilities and the features of PySpark. FREE ACCESS
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    5.  Deep Learning Frameworks
    1m 26s
    After completing this video, you will be able to list frameworks that can be used to implement deep learning, such as Keras, TensorFlow, Caffe, and PyTorch. FREE ACCESS
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    6.  Deep Learning Implementation
    3m 52s
    Learn how to implement deep learning using the Keras library. FREE ACCESS
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    7.  Data Mining and Analytical Tools
    2m 45s
    After completing this video, you will be able to list tools that can be used to implement data mining and analytics, as well as their features. FREE ACCESS
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    8.  KNIME Capabilities
    3m 1s
    In this video, learn how to build and process a data pipeline with Knime. FREE ACCESS
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    9.  Exercise: Implement Deep Learning
    1m 51s
    Learn how to set up Keras, implement a deep learning algorithm, and build data pipelines using KNIME. FREE ACCESS

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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Digital badges are yours to keep, forever.

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