Python Machine Learning (Part 4)

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Unlock modern machine learning techniques with Python by using the latest cutting-edge open source Python libraries.

This is Part 4 of the Python Machine Learning series. In this course, we will delve into the exciting subfields of machine learning — neural networks and deep learning. Using both vanilla Python and the TensorFlow library, we will explore some real world applications of deep learning algorithms.

Objectives

Understanding the architecture of neural networks Learning how to implement neural networks both from scratch and with TensorFlow. Understanding activation functions, tensors, and computation graphs Building multilayer perceptrons, regression models, deep convolutional neural networks, recurrent neural networks, and more.

Prerequisites

Python programming Understanding of basic linear algebra concepts Completion of Machine Learning Part 1, 2, 3 highly recommended Knowledge of introductory calculus (preferable, but not necessary)