Learn IT - Books tags head-first

Deep Learning with TensorFlow: Explore neural networks and build intelligent systems with Python, 2nd Edition

Packt Publishing, 2018

Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow.

Key Features

Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow

Explore deep neural...

Python Crash Course: A Hands-On, Project-Based Introduction to Programming

No Starch Press, 2015

Python Crash Course is a fast-paced, thorough introduction to Python that will have you writing programs, solving problems, and making things that work in no time.

In the first half of the book, you’ll learn about basic programming concepts, such as lists, dictionaries, classes, and loops, and practice writing...

The Joys of Hashing: Hash Table Programming with C

Apress, 2019

Build working implementations of hash tables, written in the C programming language. This book starts with simple first attempts devoid of collision resolution strategies, and moves through improvements and extensions illustrating different design ideas and approaches, followed by experiments to validate the choices. ...

Learn Keras for Deep Neural Networks: A Fast-Track Approach to Modern Deep Learning with Python

Apress, 2018

Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras.

The overall...

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

Springer, 2019

This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource...

Machine Learning Using R: With Time Series and Industry-Based Use Cases in R

Apress, 2018

Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition shows you how to work with a machine-learning algorithm and use it to build a ML model from raw data. You will see how to use R programming with TensorFlow, thus avoiding the effort of learning Python...

Beginning Data Science with Python and Jupyter: Use powerful tools to unlock actionable insights from data

Packt Publishing, 2018

Getting started with data science doesn't have to be an uphill battle. This step-by-step guide is ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction.

Key Features

Get up and running with the Jupyter ecosystem and some example datasets

...

Natural Language Processing and Computational Linguistics: A practical guide to text analysis with Python, Gensim, spaCy, and Keras

Packt Publishing, 2018

Work with Python and powerful open source tools such as Gensim and spaCy to perform modern text analysis, natural language processing, and computational linguistics algorithms.

Key Features

Discover the open source Python text analysis ecosystem, using spaCy, Gensim, scikit-learn, and...

Mathematics and Computer Science: Algorithms, Trees, Combinatorics and Probabilities (Trends in Mathematics)

Birkhauser, 2000

This is the first book where mathematics and computer science are directly confronted and joined to tackle intricate problems in computer science with deep mathematical approaches. It contains a collection of refereed papers presented at the Colloquium on Mathematics and Computer Science held at the University of Versailles-St-Quentin on...

Test-Driven Java Development - Second Edition: Invoke TDD principles for end-to-end application development

Packt Publishing, 2018

This book will teach the concepts of test driven development in Java so you can build clean, maintainable and robust code

Key Features

Explore the most popular TDD tools and frameworks and become more proficient in building applications

Create applications with better code...

Randomized Algorithms

Cambridge University Press, 1995

For many applications, a randomized algorithm is either the simplest or the fastest algorithm available, and sometimes both. This book introduces the basic concepts in the design and analysis of randomized algorithms. The first part of the text presents basic tools such as probability theory and probabilistic analysis that are frequently used in...

Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition

CRC Press, 2011

The second edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. The first edition, titled Statistical Modeling and...

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