This book is intended for those who want to learn about SQLite and how to develop apps in Swift or HTML5 using SQLite. Whether you are an expert Objective-C programmer or new to this platform, you'll learn quickly, grasping the code in real-world apps to use Swift.

Sibsankar Haldar has a PhD in Computer Science. He has extensive experience in theoretical computer science research and software development. He has been fully committed to the research and development of distributed computing, operating system, database engine and database application for the past several years. Also well known to the theoretical computer science community, S...(展开全部)

本书针对Xcode 4编写，涵盖了开发iOS应用所需知道的方方面面。从Objective-C基础知识到新增加的语言特性；从AppKit库到常见的Cocoa设计模式；从Xcode技巧到Instruments，等等。如果读者刚接触iOS编程，那么阅读本书的第一章和第二章能快让你速入门。如果读者已经 有大量的iOS编程经验，那么通读本书可以拾遗补缺。无论读者是开发新的应用，还是为应用增加新功能，十之八九能在书中找到答案或是解决思路。 除了内容全，本书的另一个特点是教读者以正确的方法解决问题。Objective-C的习惯约定有哪些（例如命名约定，内存管理约定）？创建子类时如何处理初始化方法？Cocoa的常见设计模式有哪些？如何选择数据保存方法？等等。所有这些问题，如果读者自己摸索，自己查阅散落于各处文档的知识点，难免费时费力。本书已经将这些知识整理、归纳并清...(展开全部)

Machine Learning for Finance explores new advances in machine learning and shows how they can be applied across the financial sector, including in insurance, transactions, and lending. It explains the concepts and algorithms behind the main machine learning techniques and provides example Python code for implementing the models yourself.The book is based on Jannes Klaas’ experience of running machine learning training courses for financial professionals. Rather than providing ready-made financial algorithms, the book focuses on the advanced ML concepts and ideas that can be applied in a wide variety of ways.The book shows how machine learning works on structured data, text, images, and time series. It includes coverage of generative adversarial learning, reinforcement learning, debugging, and launching machine learning products. It discusses how to fight bias in machine learning and ends with an exploration of Bayesian inference and probabilistic programming.

This book is for hobbyists who have no knowledge about programming and microcontrollers, but are keen to learn C programming using a very affordable hardware device.

If you are a forensics student, hobbyist, or professional that is seeking to increase your understanding in forensics through the use of a programming language, then this book is for you.You are not required to have previous experience in programming to learn and master the content within this book. This material, created by forensic professionals, was written with a unique perspective and understanding of examiners who wish to learn programming

Are you curious about AI? All you need is a good understanding of the Scala programming language, a basic knowledge of statistics, a keen interest in Big Data processing, and this book!

https://mml-book.github.io/ ::This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics:: The fundamental mathematical tools needed to under...(展开全部)

The interplay between optimization and machine learning is one of the most important developments in modern computational science. Optimization formulations and methods are proving to be vital in designing algorithms to extract essential knowledge from huge volumes of data. Machine learning, however, is not simply a consumer of optimization technology but a rapidly evolving fie...(展开全部)

This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well.