ISBN
9781788395762
Grasp the fundamental concepts of deep learning using Tensorflow in a hands-on manner :
This book targets data scientists and machine learning developers who wish to get started with deep learning. If you know what deep learning is but are not quite sure of how to use it, this book will help you as well. An understanding of statistics and data science concepts is required. Some familiarity with Python programming will also be beneficial.
Author/Authors: Menshawy, Ahmed
Pages: 450 | Published Date: 43159
Category: Data
ISBN
9781788293358
Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasks :
This book is targeted at data scientists and Computer Vision practitioners who wish to apply the concepts of Deep Learning to overcome any problem related to Computer Vision. A basic knowledge of programming in Pythonâ€â€and some understanding of machine learning conceptsâ€â€is required to get the best out of this book.
Author/Authors: Shanmugamani, Rajalingappaa
Pages: 310 | Published Date: 43123
Category: Data
ISBN
9781788838917
Dive deeper into neural networks and get your models trained, optimized with this quick reference guide :
If you are a Data Scientist or a Machine Learning expert, then this book is a very useful read in training your advanced machine learning and deep learning models. You can also refer this book if you are stuck in-between the neural network modeling and need immediate assistance in getting accomplishing the task smoothly. Some prior knowledge of Python and tight hold on the basics of machine learning is required.
Author/Authors: Bernico, Mike
Pages: 272 | Published Date: 43168
Category: Data
ISBN
9781787121232
Build, implement and scale distributed deep learning models for large-scale datasets :
If you are a data scientist who wants to learn how to perform deep learning on Hadoop, this is the book for you. Knowledge of the basic machine learning concepts and some understanding of Hadoop is required to make the best use of this book.
Author/Authors: Dev, Dipayan
Pages: 206 | Published Date: 42786
Category: Data
ISBN
9781787129030
Get to grips with the basics of Keras to implement fast and efficient deep-learning models :
If you are a data scientist with experience in machine learning or an AI programmer with some exposure to neural networks, you will find this book a useful entry point to deep-learning with Keras. A knowledge of Python is required for this book.
Author/Authors: Gulli, Antonio | Pal, Sujit
Pages: 318 | Published Date: 42851
Category: Data
ISBN
9781788626071
Build neural network models in text, vision and advanced analytics using PyTorch :
This book is for machine learning engineers, data analysts, data scientists interested in deep learning and are looking to explore implementing advanced algorithms in PyTorch. Some knowledge of machine learning is helpful but not a mandatory need. Working knowledge of Python programming is expected.
Author/Authors: Subramanian, Vishnu
Pages: 262 | Published Date: 43154
Category: Data
ISBN
9781786460127
Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of this comprehensive TensorFlow guide :
The book is intended for a general audience of people interested in machine learning and machine intelligence. A rudimentary level of programming in one language is assumed, as is a basic familiarity with computer science techniques and technologies, including a basic awareness of computer hardware and algorithms. Some competence in mathematics is needed to the level of elementary linear algebra and calculus
Author/Authors: Zaccone, Giancarlo | Karim, Md. Rezaul | Menshawy, Ahmed
Pages: 320 | Published Date: 42849
Category: Data
ISBN
9781786463050
Develop deep neural networks in Theano with practical code examples for image classification, machine translation, reinforcement agents, or generative models :
This book is indented to provide a full overview of deep learning. From the beginner in deep learning and artificial intelligence, to the data scientist who wants to become familiar with Theano and its supporting libraries, or have an extended understanding of deep neural nets. Some basic skills in Python programming and computer science will help, as well as skills in elementary algebra and calculus.
Author/Authors: Bourez, Christopher
Pages: 300 | Published Date: 42947
Category: Data
ISBN
9781788839303
Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more :
This book is a practical, developer-oriented introduction to deep reinforcement learning (RL). Explore the theoretical concepts of RL, before discovering how deep learning (DL) methods and tools are making it possible to solve more complex and challenging problems than ever before. Apply deep RL methods to training your agent to beat arcade games and board games, and navigate real-world environments including the stock market.
Author/Authors: Lapan, Maxim
Pages: 546 | Published Date: 43272
Category: Data
