If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Science fiction movies seem to have done Artificial Intelligence (AI) a bit of a disservice. Due to decades of popular yet farfetched sci-fi releases, when most people think of AI, they think only of evil robots taking over the planet, or perhaps friendlier (but still evil, maybe?) robots along the lines of the robot-woman in Ex Machina. In many ways, however, real-life artificial intelligence has become more interesting than in the movies, with self-driving cars redefining transportation, quantum computing reshaping how we work with large sets of data, and medical robots performing some of the most advanced surgeries known to man with astounding precision. Indeed, the future of technology in many ways belongs to AI. This means that the most exciting and important careers of the future will belong to those who possess a solid understanding of both deep learning and artificial intelligence principles.
Here is the source code for a HTML5 project that implements a machine learning algorithm in the Flappy Bird video game using neural networks and a genetic algorithm. There is used Synaptic Neural Network library to implement entire artificial neural network instead of making a new one from the scratch. Tree Class, extended Phaser Sprite class to represent a Tree sprite. Bird Class, extended Phaser Sprite class to represent a Bird sprite.
This is one of the few books that not only goes over the theory but also the step by step implementation (training your network to recognize handwritten numbers in Python) as well as testing the code and making minor tweaks to show how that will affect the overall accuracy of the network. For an added bonus, the author includes a chapter describing how you can train the network to recognize your own handwriting and things you can do to further increase the accuracy. Even though I highly recommend this book, there are a few grammatical errors as well as labels being incorrect in a few of the diagrams. You can still get through the book without the errors taking away from the content.
Neural networks are a key element of deep learning and artificial intelligence, which today is capable of some truly impressive feats. Yet too few really understand how neural networks actually work. This guide will take you on a fun and unhurried journey, starting from very simple ideas, and gradually building up an understanding of how neural networks work. You won't need any mathematics beyond secondary school, and an accessible introduction to calculus is also included. The ambition of this guide is to make neural networks as accessible as possible to as many readers as possible – there are enough texts for advanced readers already!
This course is a deep dive into details of neural network architectures with a focus on learning end-to-end models for these tasks, particularly image classification. During the 10-week course, students will learn to implement, train and debug their own neural networks and gain a detailed understanding of cutting-edge research in computer vision. In this class, students will learn to understand, implement, train, debug, visualize and potentially invent their own neural network models for a variety of language understanding tasks. Christopher has in-depth, well-explained articles with great visuals on neural networks, visualization, and convolutional neural networks.