Every month, new books are released, and we’d like to share the ones with you we think should not be missed. This time, we’re focussing on Language and Tools. Please let us know what you think, and happy reading!

Best Upcoming Language and Tools Books of September 2017

• Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
  

  Looking for complete instructions on manipulating, processing, cleaning, and crunching structured data in Python. Written by Wes McKinney, the main author of the pandas library, Python for Data Analysis also serves as a practical, modern introduction to scientific computing in Python for data-intensive applications. It’s ideal for analysts new to Python and for Python programmers new to scientific computing.

• C++ Templates: The Complete Guide (2nd Edition)
  

  Templates are among the most powerful features of C++, but they remain misunderstood and underutilized, even as the C++ language and development community have advanced. In C++ Templates, Second Edition, three pioneering C++ experts show why, when, and how to use modern templates to build software that’s cleaner, faster, more efficient, and easier to maintain. Throughout, examples clearly illustrate abstract concepts and demonstrate best practices for exploiting all that C++ templates can do.

• Programming Rust: Fast, Safe Systems Development
  

  This practical book introduces systems programmers to Rust, the new and cutting-edge language. Author Jim Blandy—a former maintainer of GNU Emacs and GNU Guile—demonstrates how Rust has the potential to be the first usable programming language that brings the benefits of an expressive modern type system to systems programming. Rust’s rules for borrowing, mutability, ownership, and moves versus copies will be unfamiliar to most systems programmers, but they’re key to Rust’s unique advantages.

• Effective Java (3rd Edition)
  

  The Definitive Guide to Java Platform Best Practices—Updated for Java 9 Java has changed dramatically since the previous edition of Effective Java was published shortly after the release of Java 6. As in previous editions, each chapter of Effective Java, Third Edition, consists of several “items,” each presented in the form of a short, stand-alone essay that provides specific advice, insight into Java platform subtleties, and updated code examples. The third edition covers language and library features added in Java 7, 8, and 9, including the functional programming constructs that were added to its object-oriented roots.

• Deep Learning with Python
  

  Deep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text-to-speech, and optical character recognition. Deep Learning with Python is structured around a series of practical code examples that illustrate each new concept introduced and demonstrate best practices. By the time you reach the end of this book, you will have become a Keras expert and will be able to apply deep learning in your own projects.

• C# 7.0 in a Nutshell: The Definitive Reference
  

  When you have questions about C# 7. NET knowledge. NET features, including XML, networking, serialization, reflection, security, application domains, and code contracts Explore the new C# 7.

• Java: The Complete Reference, Tenth Edition
  

  The Definitive Java Programming Guide Fully updated for Java SE 9, Java: The Complete Reference, Tenth Edition explains how to develop, compile, debug, and run Java programs. Bestselling programming author Herb Schildt covers the entire Java language, including its syntax, keywords, and fundamental programming principles. Swing, JavaFX, JavaBeans, and servlets are examined and numerous examples demonstrate Java in action.

• Spark: The Definitive Guide: Big Data Processing Made Simple
  

  With an emphasis on improvements and new features in Spark 2. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Spark’s scalable machine learning library. Get a gentle overview of big data and Spark Learn about DataFrames, SQL, and Datasets—Spark’s core APIs—through worked examples Dive into Spark’s low-level APIs, RDDs, and execution of SQL and DataFrames Understand how Spark runs on a cluster Debug, monitor, and tune Spark clusters and applications Learn the power of Spark’s Structured Streaming and MLlib for machine learning tasks Explore the wider Spark ecosystem, including SparkR and Graph Analysis Examine Spark deployment, including coverage of Spark in the Cloud.

• SQL for IBM i: A Database Modernization Guide
  

  This book aims to give IBM i technical users basic to intermediate SQL knowledge and tools they can use to get more out of the IBM i database. NET developers who need to “talk” to IBM i database. NET or Java Web application).

• Java 9 Modularity: Patterns and Practices for Developing Maintainable Applications
  

  The upcoming Java 9 module system will affect existing applications and offer new ways of creating modular and maintainable applications. You’ll also gain learn how to modularize existing code and how to build new Java applications in a modular way. Understand Java 9 module system concepts Master the patterns and practices for building truly modular applications Migrate existing applications and libraries to Java 9 modules Use JDK 9 tools for modular development and migration.

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