TensorFlow: Introduction to Machine Learning

TensorFlow    |    Intermediate
  • 19 Videos | 1h 40m 26s
  • Includes Assessment
  • Earns a Badge
Likes 49 Likes 49
Explore the concept of machine learning in TensorFlow, including TensorFlow installation and configuration, the use of the TensorFlow computation graph, and working with building blocks.

WHAT YOU WILL LEARN

  • describe kinds of machine learning algorithms and their use cases
    define the training and prediction phases in machine learning
    define the conceptual differences between traditional machine learning and deep learning
    compare and contrast supervised and unsupervised techniques in machine learning
    define the advantages and challenges in using TensorFlow for machine learning
    distinguish data and computations as distinct building blocks of a TensorFlow computation graph
    choose the right way to install TensorFlow based on the user's environment
    install TensorFlow and work with Jupyter Notebooks
    specify constants and build and run a computation graph
  • use TensorBoard to visualize the computation graph
    build and execute a computation graph with variables and placeholders
    visualize variables and placeholders on TensorBoard
    recognize how variables are trainable parameters and can be updated within a session
    work with feed dictionaries to input data to placeholders during training
    use named scopes to group computations
    specify and work with eager execution for prototyping and development
    recall basic concepts of machine learning and TensorFlow
    build and execute computation graphs with computation nodes and data

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    2m 9s
    UP NEXT
  • Playable
    2. 
    Introduction to Machine Learning Algorithms
    8m 21s
  • Locked
    3. 
    Understanding Machine Learning
    8m 47s
    FREE ACCESS
  • Locked
    4. 
    Understanding Deep Learning
    3m 42s
    FREE ACCESS
  • Locked
    5. 
    Supervised and Unsupervised Learning
    4m 25s
    FREE ACCESS
  • Locked
    6. 
    TensorFlow for Machine Learning
    4m 52s
    FREE ACCESS
  • Locked
    7. 
    Tensors and Operators
    7m 48s
    FREE ACCESS
  • Locked
    8. 
    Understanding How to Install TensorFlow
    5m 42s
    FREE ACCESS
  • Locked
    9. 
    Installing TensorFlow on the Local Machine
    3m 57s
    FREE ACCESS
  • Locked
    10. 
    Working with Constants
    8m 51s
    FREE ACCESS
  • Locked
    11. 
    The Computation Graph with TensorBoard
    2m 37s
    FREE ACCESS
  • Locked
    12. 
    Working with Variables and Placeholders
    8m 1s
    FREE ACCESS
  • Locked
    13. 
    Variables and Placeholders on TensorBoard
    2m 45s
    FREE ACCESS
  • Locked
    14. 
    Updating Variables in a Session
    4m 40s
    FREE ACCESS
  • Locked
    15. 
    Feed Dictionaries
    7m 46s
    FREE ACCESS
  • Locked
    16. 
    Named Scopes for Better Visualization
    2m 25s
    FREE ACCESS
  • Locked
    17. 
    Eager Execution
    4m 46s
    FREE ACCESS
  • Locked
    18. 
    Exercise: Machine Learning and TensorFlow
    5m 9s
    FREE ACCESS
  • Locked
    19. 
    Exercise: Working with Computation Graph
    3m 45s
    FREE ACCESS

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