Machine Learning for KidsArtificial intelligence (AI) is the ability of computers to simulate human thinking. Machine learning (ML) is one of the building blocks of AI. It's based on the idea that computers can be taught to do things on their own from the data and feedback you give them.
Machine Learning for Kids consists of this book and a kid-friendly companion website paired with the educational coding platform, Scratch. Together, they provide an easy-to-use guided programming environment for adding ML capabilities to your own AI projects!
As you work through each chapter you'll discover how ML systems can be taught to recognize text, images, numbers, and sounds, and different ways of training ML models to improve their accuracy. You'll turn your models into fun computer games and apps (and see what happens when an AI system gets confused by bad data) while building:
- A Rock, Paper, Scissors game that knows your hand shapes;
- A smart question-answering chatbot;
- A computer character that reacts ...
Algorithmic ThinkingAlgorithmic Thinking will teach you how to solve challenging programming problems and design your own algorithms. Daniel Zingaro, a master teacher, draws his examples from world-class programming competitions like USACO and IOI. You'll learn how to classify problems, choose data structures, and identify appropriate algorithms. You'll also learn how your choice of data structure, whether a hash table, heap, or tree, can affect runtime and speed up your algorithms; and how to adopt powerful strategies like recursion, dynamic programming, and binary search to solve challenging problems.
Line-by-line breakdowns of the code will teach you how to use algorithms and data structures like:
- The breadth-first search algorithm to find the optimal way to play a board game or find the best way to translate a book;
- Dijkstra's algorithm to determine how many mice can exit a maze or the number of fastest routes between two locations;
- The union-find data structure to answer questions about c ...
How Computers Really WorkHow Computers Really Work is a hands-on guide to the computing ecosystem: everything from circuits to memory and clock signals, machine code, programming languages, operating systems, and the internet.
But you won't just read about these concepts, you'll test your knowledge with exercises, and practice what you learn with 41 optional hands-on projects. Build digital circuits, craft a guessing game, convert decimal numbers to binary, examine virtual memory usage, run your own web server, and more.
Explore concepts like how to:
- Think like a software engineer as you use data to describe a real world concept;
- Use Ohm's and Kirchhoff's laws to analyze an electrical circuit;
- Think like a computer as you practice binary addition and execute a program in your mind, step-by-step.
The book's projects will have you translate your learning into action, as you:
- Learn how to use a multimeter to measure resistance, current, and voltage;
- Build a half adder to see how logical op ...
Beyond the Basic Stuff with PythonYou've completed a basic Python programming tutorial or finished Al Sweigart's best selling Automate the Boring Stuff with Python. What's the next step toward becoming a capable, confident software developer?
Welcome to Beyond the Basic Stuff with Python. More than a mere collection of advanced syntax and masterful tips for writing clean code, you'll learn how to advance your Python programming skills by using the command line and other professional tools like code formatters, type checkers, linters, and version control. Sweigart takes you through best practices for setting up your development environment, naming variables, and improving readability, then tackles documentation, organization and performance measurement, as well as object-oriented design and the Big-O algorithm analysis commonly used in coding interviews. The skills you learn will boost your ability to program - not just in Python but in any language.
You'll learn:
- Coding style, and how to use Python's Black aut ...
Build Location-Based Projects for iOSCoding is awesome. So is being outside. With location-based iOS apps, you can combine the two for an enhanced outdoor experience. Use Swift to create your own apps that use GPS data, read sensor data from your iPhone, draw on maps, automate with geofences, and store augmented reality world maps. You'll have a great time without even noticing that you're learning. And even better, each of the projects is designed to be extended and eventually submitted to the App Store. Explore, share, and have fun.
Location-based apps are everywhere. From mapping our jogging path to pointing us to the nearest collectible creature in a location-based game, these apps offer useful and interesting features and information related to where you are. Using real-world maps and places as the environment, they add an extra layer of adventure to exploring the outdoors. If you've ever wanted to make your own location-based apps and games, you can learn how with four simple, Swift-based projects that are easy t ...
Deep Reinforcement Learning in UnityGain an in-depth overview of reinforcement learning for autonomous agents in game development with Unity.
This book starts with an introduction to state-based reinforcement learning algorithms involving Markov models, Bellman equations, and writing custom C# code with the aim of contrasting value and policy-based functions in reinforcement learning. Then, you will move on to path finding and navigation meshes in Unity, setting up the ML Agents Toolkit (including how to install and set up ML agents from the GitHub repository), and installing fundamental machine learning libraries and frameworks (such as Tensorflow). You will learn about: deep learning and work through an introduction to Tensorflow for writing neural networks (including perceptron, convolution, and LSTM networks), Q learning with Unity ML agents, and porting trained neural network models in Unity through the Python-C# API. You will also explore the OpenAI Gym Environment used throughout the book.
Deep Reinforcement ...
Terraform in ActionTerraform in Action introduces the infrastructure-as-code (IaC) model that lets you instantaneously create new components and respond efficiently to changes in demand. You'll use the Terraform automation tool to design and manage servers that can be provisioned, shared, changed, tested, and deployed with a single command.
Provision, deploy, scale, and clone your entire stack to the cloud at the touch of a button. In Terraform, you create a collection of simple declarative scripts that define and manage application infrastructure. This powerful infrastructure-as-code approach automates key tasks like versioning and testing for everything from low-level networking to cloud services.
Terraform in Action shows you how to automate and scale infrastructure programmatically using the Terraform toolkit. Using practical, relevant examples, you'll use Terraform to provision a Kubernetes cluster, deploy a multiplayer game, and configure other hands-on projects. As you progress to advanced t ...
Adversarial Tradecraft in CybersecurityLittle has been written about what to do when live hackers are on your system and running amok. Even experienced hackers tend to choke up when they realize the network defender has caught them and is zoning in on their implants in real time. This book will provide tips and tricks all along the kill chain of an attack, showing where hackers can have the upper hand in a live conflict and how defenders can outsmart them in this adversarial game of computer cat and mouse.
This book contains two subsections in each chapter, specifically focusing on the offensive and defensive teams. It begins by introducing you to adversarial operations and principles of computer conflict where you will explore the core principles of deception, humanity, economy, and more about human-on-human conflicts. Additionally, you will understand everything from planning to setting up infrastructure and tooling that both sides should have in place.
Throughout this book, you will learn how to gain an advantage ove ...
AI for Healthcare with Keras and Tensorflow 2.0Learn how AI impacts the healthcare ecosystem through real-life case studies with TensorFlow 2.0 and other machine learning (ML) libraries.
This book begins by explaining the dynamics of the healthcare market, including the role of stakeholders such as healthcare professionals, patients, and payers. Then it moves into the case studies. The case studies start with EHR data and how you can account for sub-populations using a multi-task setup when you are working on any downstream task. You also will try to predict ICD-9 codes using the same data. You will study transformer models. And you will be exposed to the challenges of applying modern ML techniques to highly sensitive data in healthcare using federated learning. You will look at semi-supervised approaches that are used in a low training data setting, a case very often observed in specialized domains such as healthcare. You will be introduced to applications of advanced topics such as the graph convolutional network and how you c ...
Just Enough RIf your job involves working with data in any manner, you cannot afford to ignore the R revolution! If your domain is called data analysis, analytics, informatics, data science, reporting, business intelligence, data management, big data, or visualization, you just have to learn R as this programming language is a game-changing sledgehammer.
However, if you have looked at a standard text on R or read some of the online discussions, you might feel that there is a steep learning curve of six months or more to grok the language. I will debunk this myth through my book by focusing on practical essentials instead of theory.
If you have programmed in some language in the past (whether that language be SAS, SPSS, C, C++, C#, Java, Python, Perl, Visual Basic, Ruby, Scala, shell scripts, or plain old SQL), even if you are rusty, this book will get you up and running with R in a single day, writing programs for data analysis and visualization. ...