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Building Regression Models Using TensorFlow

Course Summary

TensorFlow is the tool of choice for building deep learning applications. In this course, you'll learn how the neurons in neural networks learn non-linear functions, and how neural networks execute operations such as regression and classification.


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    Course Syllabus

    Course Overview
    - 1m 35s

    —Course Overview 1m 35s
    Learning Using Neurons
    - 45m 56s

    —Understanding Deep Learning 5m 3s
    —Deep Learning as a Representation Learning System 5m 14s
    —Neurons as Learning Units 4m 25s
    —Understanding a Neuron 7m 38s
    —Activation Functions 2m 23s
    —Regression: The Simplest Neural Network 4m 58s
    —XOR: A Slightly More Complex Neural Network 7m 27s
    —Learning XOR 5m 1s
    —Choice of Activation Function 2m 20s
    —Prequisites and Course Outline 1m 23s
    Building Linear Regression Models Using TensorFlow
    - 46m 43s
    Building Logistic Regression Models Using TensorFlow
    - 43m 28s
    Building Generalized Linear Models Using Estimators
    - 21m 51s


Course Fee:
USD 29

Course Type:

Self-Study

Course Status:

Active

Workload:

1 - 4 hours / week

This course is listed under Networks & IT Infrastructure Community

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