Keras is an open source neural network library written in Python. It is capable of running on top of MXNet, Deep learning Tensorflow, CNTK, or Theano. Designed to enable fast experimentation with deep neural networks, it focuses on being minimal, modular, and extensible.
This course provides a comprehensive expert level details in deep learning(Keras). We start by a brief recap of the most common concepts found in machine learning. Then, we introduce neural networks and the optimization techniques to train them. We’ll show you how to get ready with Keras API to start training deep learning models, both on CPU and on GPU. Then, we present two types of neural architecture: convolutional and recurrent neural networks
In this course, we will start from the very scratch. This is a very applied course, so we will immediately start coding even without installation! You will see a brief bit of absolutely essential theory and then we will get into the environment setup and explain almost all concepts through code. You will be using Keras -- one of the easiest and most powerful machine learning tools out there.
In this course we will get started with Keras, where we'll compare with TensorFlow to make it easier to understand, and to build your knowledge upon itself. By connecting new information with existing knowledge, you'll form stronger connections in your brain on all of this valuable tech content. You'll learn where and how to use Keras. By the end of this course you'll have such a solid grasp you can add all of these technologies as qualifications on your resume, LinkedIn profile, or personal website.
Also we will learn to build a basic image recognition model and much much more.