Deep Learning with Keras

Deep Learning with Keras

English | MP4 | AVC 1920×1080 | AAC 44KHz 2ch | 1h 21m | 376 MB

Get to grips with the basics of Keras to implement fast and efficient deep-learning models

Keras is a high-level neural network library written in Python, and runs on top of either Theano or TensorFlow. It is a minimal, highly modular framework that runs on both CPUs and GPUs, and allows you to put your ideas into action in the shortest possible time. This course will help you get started with the basics of Keras, in a highly practical manner.

This course is an easy-to-follow guide full of examples and real-world applications to help you gain an in-depth understanding of Keras. This course showcases working Deep Neural Networks coded in Python using Keras.

What You Will Learn

  • Learn backpropagation
  • Install and configure Keras
  • Understand callbacks and for customizing the process
  • Study deep convolutional neural networks
  • Recognize CIFAR-10 images with deep learning
Table of Contents

01 – The Course Overview
02 – Perceptron
03 – Building a Network to Recognize Handwritten Numbers
04 – Playing Around with the Parameters to Improve Performance
05 – Installing and Configuring Keras
06 – Keras API
07 – Callbacks for Customizing the Training Process
08 – Deep Convolutional Neural Network – DCNN
09 – Recognizing CIFAR-10 Images with Deep Learning