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.

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.

This book is for children aged 9 and up, and their parents, who may or may not have a technical background. This book is tailored around the central idea of introducing electronics as a fun and a curiosity-inducing exercise. This book can act as a bonding exercise between parent and child over a single weekend.

This book is for children aged 9 and up, and their parents, who may or may not have a technical background. This book is tailored around the central idea of introducing electronics as a fun and a curiosity-inducing exercise. This book can act as a bonding exercise between parent and child over a single weekend.

This is the book for you if you are a student, hobbyist, developer, or designer with little or no programming and hardware prototyping experience, and you want to develop IoT applications.If you are a software developer or a hardware designer and want to create connected devices applications, then this book will help you get started.

This book is for Arduino programmers with intermediate experience of developing projects, and who want to extend their knowledge by building projects for secret agents. It would also be great for other programmers who are interested in learning about electronics and programming on the Arduino platform.

If you are a C++ programmer who has never used Boost libraries before, this book will get you up-to-speed with using them. Whether you are developing new C++ software or maintaining existing code written using Boost libraries, this hands-on introduction will help you decide on the right library and techniques to solve your practical programming problems.

This book is for C++ developers comfortable with OOP who are interested in learning how to apply the functional paradigm to create robust and testable apps.

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.

Machine learning presents an entirely unique opportunity in software development. It allows smartphones to produce an enormous amount of useful data that can be mined, analyzed, and used to make predictions. This book will help you master machine learning for mobile devices with easy-to-follow, practical examples.You will begin with an introduction to machine learning on mobiles and grasp the fundamentals so you become well-acquainted with the subject. You will master supervised and unsupervised learning algorithms, and then learn how to build a machine learning model using mobile-based libraries such as Core ML, TensorFlow Lite, ML Kit, and Fritz on Android and iOS platforms. In doing so, you will also tackle some common and not-so-common machine learning problems with regard to Computer Vision and other real-world domains.By the end of this book, you will have explored machine learning in depth and implemented on-device machine learning with ease, thereby gaining a thorough understanding of how to run, create, and build real-time machine-learning applications on your mobile devices.