Keras Deep Learning & Generative Adversarial Networks (GAN)

About this course

Hi There!

Hello and welcome to my new course Deep Learning with Generative Adversarial Networks (GAN). This course is divided into two halves. In the first half we will deal with Deep Learning and Neural Networks and in the second half on top of that, we will continue with Generative Adversarial Networks or GAN or we can call it as 'gan'. So lets see what are the topics that are included in each module. At first, the Deep Learning one..As you already know the artificial intelligence domain is divided broadly into deep learning and machine learning. In-fact deep learning is machine learning itself but Deep learning with its deep neural networks and algorithms try to learn high-level features from data without human intervention. That makes deep learning the base of all future self intelligent systems.

I am starting from the very basic things to learn like learning the programming language basics and other supporting libraries at first and proceed with the core topic. Let's see what are the interesting topics included in this course. At first we will have an introductory theory session about Artificial Intelligence, Machine learning, Artificial Neurons based Deep Learning and Neural Networks. After that, we are ready to proceed with preparing our computer for python coding by downloading and installing the anaconda package and will check and see if everything is installed fine. We will be using the browser based IDE called Jupyter notebook for our further coding exercises.

I know some of you may not be coming from a python based programming background. The next few sessions and examples will help you get the basic python programming skill to proceed with the sessions included in this course. The topics include Python assignment, flow-control, functions List and Tuples, Dictionaries, Functions etc. Then we will start with learning the basics of the Python Numpy library which is used to adding

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