Description

There is a strong demand for machine learning (DL) skills and expertise to solve challenging business problems globally and locally in KSA. This course will help learners build capacity in core DL tools and methods and enable them to develop their deep-learning applications. This course covers the basic theory behind DL algorithms, but the majority of the focus is on hands-on examples using PyTorch.

Learning Objectives

The primary learning objective of this course is to provide students with practical, hands-on experience with state-of-the-art machine learning and deep learning tools widely used in industry.

This course covers portions of chapters 10-19 of Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow and chapters 11-19 of Machine Learning with PyTorch and Scikit-Learn. The following topics will be discussed.

* Introduction to Artificial Neural Networks (ANNs)

* Training Deep Neural Networks (DNNs)

* Custom Models and Training with PyTorch and Lightning

* Strategies for Loading and Preprocessing Data * Training and Deploying PyTorch Models at Scale