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Machine Learning and Security: Protecting Systems with Data and Algorithms
Machine Learning and Security: Protecting Systems with Data and Algorithms

Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you’ll explore ways to apply machine learning to security...

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...

Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists
Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists

Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. Each chapter guides you...

Efficient Algorithms for Listing Combinatorial Structures (Distinguished Dissertations in Computer Science)
Efficient Algorithms for Listing Combinatorial Structures (Distinguished Dissertations in Computer Science)

This thesis is concerned with the design of efficient algorithms for listing combinatorial structures. The research described here gives some answers to the following questions: which families of combinatorial structures have fast computer algorithms for listing their members, What general methods are useful for listing combinatorial...

Efficient Algorithms for Listing Combinatorial Structures (Distinguished Dissertations in Computer Science)
Efficient Algorithms for Listing Combinatorial Structures (Distinguished Dissertations in Computer Science)

This thesis is concerned with the design of efficient algorithms for listing combinatorial structures. The research described here gives some answers to the following questions: which families of combinatorial structures have fast computer algorithms for listing their members, What general methods are useful for listing combinatorial...

Scheduling: Theory, Algorithms, and Systems
Scheduling: Theory, Algorithms, and Systems

Sequencing and scheduling is a formof decision-making that plays a crucial role in manufacturing and service industries. In the current competitive environment effective sequencing and scheduling has become a necessity for survival in the market-place. Companies have to meet shipping dates that have been committed to customers, as failure to...

Deep Learning with Python: A Hands-on Introduction
Deep Learning with Python: A Hands-on Introduction
Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of these frameworks is often...
Practical Statistics for Data Scientists: 50 Essential Concepts
Practical Statistics for Data Scientists: 50 Essential Concepts

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their...

Introducing Data Science: Big Data, Machine Learning, and more, using Python tools
Introducing Data Science: Big Data, Machine Learning, and more, using Python tools

Summary

Introducing Data Science teaches you how to accomplish the fundamental tasks that occupy data scientists. Using the Python language and common Python libraries, you'll experience firsthand the challenges of dealing with data at scale and gain a solid foundation in data science.

...

The New Shop Class: Getting Started with 3D Printing, Arduino, and Wearable Tech
The New Shop Class: Getting Started with 3D Printing, Arduino, and Wearable Tech

The New Shop Class connects the worlds of the maker and hacker with that of the scientist and engineer. If you are a parent or educator or a budding maker yourself, and you feel overwhelmed with all of the possible technologies, this book will get you started with clear discussions of what open source technologies like 3D printers,...

Processing Big Data with Azure HDInsight: Building Real-World Big Data Systems on Azure HDInsight Using the Hadoop Ecosystem
Processing Big Data with Azure HDInsight: Building Real-World Big Data Systems on Azure HDInsight Using the Hadoop Ecosystem
Get a jump start on using Azure HDInsight and Hadoop Ecosystem components. As most Hadoop and Big Data projects are written in either Java, Scala, or Python, this book minimizes the effort to learn another language and is written from the perspective of a .NET developer. Hadoop components are covered, including Hive, Pig, HBase, Storm,...
The Stars of Galileo Galilei and the Universal Knowledge of Athanasius Kircher
The Stars of Galileo Galilei and the Universal Knowledge of Athanasius Kircher

In this fascinating book, the author traces the careers, ideas, discoveries, and inventions of two renowned scientists, Athanasius Kircher and Galileo Galilei, one a Jesuit, the other a sincere man of faith whose relations with the Jesuits deteriorated badly. The Author documents Kircher’s often intuitive work in many areas, including...

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