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TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning
TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning

Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects...

Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning
Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning

This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or...

Introduction to Machine Learning with R: Rigorous Mathematical Analysis
Introduction to Machine Learning with R: Rigorous Mathematical Analysis

Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory guide will help you gain a solid foundation in machine learning principles. Using the R programming language, you’ll first start to learn with regression modelling and then move into more...

Applied Text Analysis with Python: Enabling Language-Aware Data Products with Machine Learning
Applied Text Analysis with Python: Enabling Language-Aware Data Products with Machine Learning

From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural...

Java: Data Science Made Easy
Java: Data Science Made Easy

Data collection, processing, analysis, and more

About This Book

  • Your entry ticket to the world of data science with the stability and power of Java
  • Explore, analyse, and visualize your data effectively using easy-to-follow examples
  • A highly practical course covering a broad...
Neural Networks and Pattern Recognition
Neural Networks and Pattern Recognition
This book is one of the most up-to-date and cutting-edge texts available on the rapidly growing application area of neural networks. Neural Networks and Pattern Recognition focuses on the use of neural networksin pattern recognition, a very important application area for neural networks technology. The contributors are widely known...
Embedded Robotics: Mobile Robot Design and Applications with Embedded Systems
Embedded Robotics: Mobile Robot Design and Applications with Embedded Systems

This book presents a unique combination of mobile robots and embedded systems, from introductory to intermediate level. It is structured in three parts, dealing with embedded systems (hardware and software design, actuators, sensors, PID control, multitasking), mobile robot design (driving, balancing, walking, and flying robots), and mobile...

Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms
Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms

With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field.

...
Machine Learning in Computer Vision (Computational Imaging and Vision)
Machine Learning in Computer Vision (Computational Imaging and Vision)
The goal of computer vision research is to provide computers with humanlike
perception capabilities so that they can sense the environment, understand
the sensed data, take appropriate actions, and learn from this experience in
order to enhance future performance. The field has evolved from the application
of classical pattern
...
R Deep Learning Essentials
R Deep Learning Essentials

Key Features

  • Harness the ability to build algorithms for unsupervised data using deep learning concepts with R
  • Master the common problems faced such as overfitting of data, anomalous datasets, image recognition, and performance tuning while building the models
  • Build models relating to neural...
Mobile Robots: The Evolutionary Approach (Studies in Computational Intelligence)
Mobile Robots: The Evolutionary Approach (Studies in Computational Intelligence)
The design and control of autonomous intelligent mobile robotic systems operating in unstructured changing environments includes many objective difficulties. There are several studies about the ways in which, robots exhibiting some degree of autonomy, adapt themselves to fit in their environments. The application and use of bio-inspired and...
Adaptive Business Intelligence
Adaptive Business Intelligence
From the reviews of the first edition: 

"In this book the authors explain the science and application of numerous prediction and optimization techniques as well as how these concepts can be used to develop adaptive decision-making systems. The book is suitable for business and IT managers who make decisions in complex industrial and...

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