What you'll learn

Building Neural Networks with Tensorflow

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:

You want to get into machine learning and artificial neural networks

You already work in ML/AI and need to learn Tensorflow

You are a student, know some coding, and want to get into machine learning



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