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Mastering .NET Machine Learning
Mastering .NET Machine Learning

About This Book

  • Based on .NET framework 4.6.1, includes examples on ASP.NET Core 1.0
  • Set up your business application to start using machine learning techniques
  • Familiarize the user with some of the more common .NET libraries for machine learning
  • Implement...
Java for Data Science
Java for Data Science
Examine the techniques and Java tools supporting the growing field of data science 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 Make your Java applications more capable using machine learning Who This Book Is...
Deep Learning: Practical Neural Networks with Java
Deep Learning: Practical Neural Networks with Java

Build and run intelligent applications by leveraging key Java machine learning libraries

About This Book

  • Develop a sound strategy to solve predictive modelling problems using the most popular machine learning Java libraries.
  • Explore a broad variety of data processing, machine learning,...
Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

Graphics in this book are printed in black and white.

Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data....

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...

Classification and Learning Using Genetic Algorithms: Applications in Bioinformatics and Web Intelligence (Natural Computing Series)
Classification and Learning Using Genetic Algorithms: Applications in Bioinformatics and Web Intelligence (Natural Computing Series)
Genetic algorithms (GAs) are randomized search and optimization techniques guided by the principles of evolution and natural genetics; they have a large amount of implicit parallelism. GAs perform multimodal search in complex landscapes and provide near-optimal solutions for objective or tness func tion of an...
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...

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...

Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs)
Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs)
The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. “Big data,” “data science,” and “machine learning” have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science...
Artificial Intelligence: First CCF International Conference, ICAI 2018, Jinan, China, August 9-10, 2018, Proceedings (Communications in Computer and Information Science)
Artificial Intelligence: First CCF International Conference, ICAI 2018, Jinan, China, August 9-10, 2018, Proceedings (Communications in Computer and Information Science)
This book constitutes the refereed proceedings of the First CCF International Conference on Artificial Intelligence, CCF-ICAI 2018, held in Jinan, China in August, 2018.  The 17 papers presented were carefully reviewed and selected from 82 submissions. The papers are organized in topical sections on unsupervised...
MATLAB Deep Learning: With Machine Learning, Neural Networks and Artificial Intelligence
MATLAB Deep Learning: With Machine Learning, Neural Networks and Artificial Intelligence
Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MATLAB Deep Learning employs MATLAB as the underlying programming...
Static and Dynamic Neural Networks: From Fundamentals to Advanced Theory
Static and Dynamic Neural Networks: From Fundamentals to Advanced Theory
With the evolution of our complex technological society and the introduction of new notions and innovative theoretical tools in the field of intelligent systems, the field of neural networks is undergoing an enormous evolution. These evolving and innovative theoretical tools are centered around the theory of soft computing, a theory that embodies...
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