Key Features
- Covers the latest concepts in Python deep learning
- Introduction to Tensorflow
- Full of examples of solving complicated tasks
Book Description
Deep learning is currently one of the best providers of solutions regarding problems in image recognition, speech recognition, object recognition, and natural language with its increasing number of libraries that are available in Python.
This book takes you from basic calculus knowledge to understanding backpropagation and its application for training in neural networks for deep learning and understanding automatic differentiation. Through the course, we will provide a thorough training in convolutional, recurrent neural networks and focus on supervised learning and integration into your product offerings such as search, image recognition, and object processing. We will also examine the performance of the sentimental analysis model and will conclude with an introduction to Tensorflow.
By the end of this book, you will be able to confidently start working with deep learning right away.
What you will learn
- Get the lowdown on backpropagation
- Perceive and understand automatic differentiation with Theano
- Explore the powerful mechanism of seamless CPU and GPU usage with Theano
- Apply convolutional neural networks for image analysis
- Discover the methods of image classification and harness object recognition using deep learning
- Get to know recurrent neural networks for the textual sentimental analysis model