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A Primer
What you'll learn
Requirements
Description
You're going to learn the most popular library to build networks and machine learning algorithms.
In this hands-on, practical course, you will be working your way through with Python, Tensorflow, and Jupyter notebooks.
What you will learn:
Basics of Tensorflow
Artificial Neurons
Feed Forward Neural Networks
Activations and Softmax Output
Gradient Descent
Backpropagation
Loss Function
MSE
Model Optimization
Cross-Entropy
Linear Regression
Logistic Regression
Convolutional Neural Networks (with examples)
Text and Sequence Data
Recurrent Neural Networks (with examples)
Neural Style Transfer (in progress)
Who this course is for:
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