Windows Phone 7 XNA Cookbook. Over 70 recipes for making your own games with this Microsoft Windows Phone 7 XNA book and

Zheng Yang

Developing games for Windows Phone 7, a new mobile platform, is your big chance to impact the world of mobile games. The XNA 4.0 for Windows Phone 7 integrates a lot of capabilities from software and hardware for you to create incredible games. The next generation of mobile games will be built by you. Windows Phone 7 XNA Cookbook is the best choice for you to make a game on Windows Phone 7. The book helps you to master the indispensable techniques to create your games using XNA 4.0. From the basics such as animating a 2D sprite and interacting with the customized graphical user interface to the more challenging such as 3D graphic rendering and collision detection.This comprehensive cookbook covers all the essential areas of XNA game development for Windows Phone 7, such as approaches to control the sensors, gestures and typical kinds of cameras. We also have recipes for sprite animation, texture rendering, and graphical user interface development that will give you a powerful tool to work with 2D effects. After this we move onto the more juicy stuff with recipes covering 3D graphic rendering and collision detection, and major ways to improve your loading efficiency. You will also work with Xbox live so you can take your game global. Finally, no mobile game development book would be complete without a look at performance optimization to make your games run faster. Windows Phone 7 XNA Cookbook will equip you with the firepower to rock the game world.

Learning Phalcon PHP. Learn Phalcon interactively and build high-performance web applications

Calin Rada, Ioan C Rada

Mastering PyCharm. Use PyCharm with fluid efficiency to write idiomatic python code

Nafiul Islam

PhpStorm Cookbook. Discover over 80 recipes to learn how to build and test PHP applications efficiently using the PhpStorm IDE

Mukund Chaudhary

Applying and Extending Oracle Spatial. This guide takes you straight into the attributes of Oracle Spatial and teaches you to extend, apply, and combine them with other Oracle and open source technologies. A vital manual for solving everyday problems

Siva Ravada, Simon Greener

Spatial applications should be developed in the same way that users develop other database applications: by starting with an integrated data model in which the SDO_GEOMETRY objects are just another attribute describing entities and by using as many of the database features as possible for managing the data. If a task can be done using a database feature like replication, then it should be done using the standard replication technology instead of inventing a new procedure for replicating spatial data. Sometimes solving a business problem using a PL/SQL function can be more powerful, accessible, and easier to use than trying to use external software. Because Oracle Spatial's offerings are standards compliant, this book shows you how Oracle Spatial technology can be used to build cross-vendor database solutions. Applying and Extending Oracle Spatial shows you the clever things that can be done not just with Oracle Spatial on its own, but in combination with other database technologies. This is a great resource book that will convince you to purchase other Oracle technology books on non-spatial specialist technologies because you will finally see that spatial is not special: it is a small, fun, and clever part of a much larger whole.

Practical Machine Learning. Learn how to build Machine Learning applications to solve real-world data analysis challenges with this Machine Learning book – packed with practical tutorials

Sunila Gollapudi

This book explores an extensive range of machine learning techniques uncovering hidden tricks and tips for several types of data using practical and real-world examples. While machine learning can be highly theoretical, this book offers a refreshing hands-on approach without losing sight of the underlying principles. Inside, a full exploration of the various algorithms gives you high-quality guidance so you can begin to see just how effective machine learning is at tackling contemporary challenges of big dataThis is the only book you need to implement a whole suite of open source tools, frameworks, and languages in machine learning. We will cover the leading data science languages, Python and R, and the underrated but powerful Julia, as well as a range of other big data platforms including Spark, Hadoop, and Mahout. Practical Machine Learning is an essential resource for the modern data scientists who want to get to grips with its real-world application.With this book, you will not only learn the fundamentals of machine learning but dive deep into the complexities of real world data before moving on to using Hadoop and its wider ecosystem of tools to process and manage your structured and unstructured data. You will explore different machine learning techniques for both supervised and unsupervised learning; from decision trees to Naïve Bayes classifiers and linear and clustering methods, you will learn strategies for a truly advanced approach to the statistical analysis of data. The book also explores the cutting-edge advancements in machine learning, with worked examples and guidance on deep learning and reinforcement learning, providing you with practical demonstrations and samples that help take the theory–and mystery–out of even the most advanced machine learning methodologies.

50 Algorithms Every Programmer Should Know. Tackle computer science challenges with classic to modern algorithms in machine learning, software design, data systems, and cryptography - Second Edition

Imran Ahmad, Somaieh Nikpoor

The ability to use algorithms to solve real-world problems is a must-have skill for any developer or programmer. This book will help you not only to develop the skills to select and use an algorithm to tackle problems in the real world but also to understand how it works.You'll start with an introduction to algorithms and discover various algorithm design techniques, before exploring how to implement different types of algorithms, with the help of practical examples. As you advance, you'll learn about linear programming, page ranking, and graphs, and will then work with machine learning algorithms to understand the math and logic behind them.Case studies will show you how to apply these algorithms optimally before you focus on deep learning algorithms and learn about different types of deep learning models along with their practical use.You will also learn about modern sequential models and their variants, algorithms, methodologies, and architectures that are used to implement Large Language Models (LLMs) such as ChatGPT.Finally, you'll become well versed in techniques that enable parallel processing, giving you the ability to use these algorithms for compute-intensive tasks.By the end of this programming book, you'll have become adept at solving real-world computational problems by using a wide range of algorithms.

Business Intelligence with Databricks SQL. Concepts, tools, and techniques for scaling business intelligence on the data lakehouse

Vihag Gupta

In this new era of data platform system design, data lakes and data warehouses are giving way to the lakehouse – a new type of data platform system that aims to unify all data analytics into a single platform. Databricks, with its Databricks SQL product suite, is the hottest lakehouse platform out there, harnessing the power of Apache Spark™, Delta Lake, and other innovations to enable data warehousing capabilities on the lakehouse with data lake economics.This book is a comprehensive hands-on guide that helps you explore all the advanced features, use cases, and technology components of Databricks SQL. You’ll start with the lakehouse architecture fundamentals and understand how Databricks SQL fits into it. The book then shows you how to use the platform, from exploring data, executing queries, building reports, and using dashboards through to learning the administrative aspects of the lakehouse – data security, governance, and management of the computational power of the lakehouse. You’ll also delve into the core technology enablers of Databricks SQL – Delta Lake and Photon. Finally, you’ll get hands-on with advanced SQL commands for ingesting data and maintaining the lakehouse.By the end of this book, you’ll have mastered Databricks SQL and be able to deploy and deliver fast, scalable business intelligence on the lakehouse.