Publisher's Synopsis
★★Buy the Paperback Version of this Book and get the Kindle Book version for FREE ★★
You to participate in the revolution that brings artificial intelligence back to the heart of our society, thanks to data scientists.
Data science consists in translating problems of any other nature into quantitative modeling problems, solved by processing algorithms.
This book, designed for anyone wishing to learn Deep Learning. This book presents the main techniques: deep neural networks, able to model all kinds of data, convolution networks, able to classify images, segment them and discover the objects or people who are there, recurring networks, it contains sample code so that the reader can easily test and run the programs.
- Deep learning
- Neural Networks and Deep Learning
- Deep Learning Parameters and Hyper-parameters
- Deep Neural Networks Layers
- Deep Learning Activation Functions
- Convolutional Neural Network
- Python Data Structures
- Best practices in Python and Zen of Python
- Installing Python
- Python
These are some of the topics covered in this book:
- fundamentals of deep learning
- fundamentals of probability
- fundamentals of statistics
- fundamentals of linear algebra
- introduction to machine learning and deep learning
- fundamentals of machine learning
- fundamentals of neural networks and deep learning
- deep learning parameters and hyper-parameters
- deep neural networks layers
- deep learning activation functions
- convolutional neural network
- Deep learning in practice (in jupyter notebooks)
- python data structures
- best practices in python and zen of python
- installing python
- To help you understand deep learning in detail
- To help you know how to get started with deep learning in Python by setting up the coding environment.
- To help you transition from a deep learning Beginner to a Professional.
- To help you learn how to develop a complete and functional artificial neural network
- model in Python on your own. And more
