Best of
Artificial-Intelligence

1

Machine Learning Yearning


Andrew Ng
    But building a machine learning system requires that you make practical decisions: Should you collect more training data? Should you use end-to-end deep learning? How do you deal with your training set not matching your test set? and many more. Historically, the only way to learn how to make these "strategy" decisions has been a multi-year apprenticeship in a graduate program or company. This is a book to help you quickly gain this skill, so that you can become better at building AI systems.

Jad-Chetan


Harkisan Mehta
    The main characters are Chintan and Tulsi.

Core Python Programming


R. Nageswara Rao
    Nageswara Rao, Wiley India, 9789351199427

Acheron Rising


Ken Lozito
    Outclassed and outgunned, Elias must find a way to stop a superior enemy fleet from enslaving his people, but how can he succeed where every other star union in the galaxy has failed? Acheron Rising is a military science fiction novella that introduces the Federation Chronicles universe by Ken Lozito.—-The novella also includes the first chapter(sneak peek) from Acheron Inheritance - Federation Chronicles Book 1, which is available on pre-order.

Quantum Computing Algorithms for Artificial Intelligence


Amit Ray
    There are number of breakthrough applications in recent years. The main aim of the book is to bridge classical and quantum machine learning algorithms within a unified framework of the latest development on quantum computers. The book examined limitations and advantages of different machine learning algorithms in classical and quantum computing frameworks. It explained the ways to leverage the quantum properties of superposition, entanglement, and tunneling in the context of machine learning and artificial intelligence applications. The book explained in depth the concepts of Quantum Algorithms, Quantum Programming, Quantum Neural Networks, Quantum Parametric Circuits, Quantum back-propagation principles, Quantum Support Vector Machines, Quantum CNN, Quantum Restricted Boltzmann Machines, Quantum LSTM, Quantum RNN, Quantum Deep Learning and Quantum Reinforcement Learning. It also explains the details of Quantum Principal Component Analysis, Quantum State Learning, Quantum Meta-Learning (QML), Quantum Dynamical Descent (QDD), Quantum Approximate Optimization Algorithm (QAOA), Quantum Adiabatic Algorithm (QAA). Finally, the book discuses the Quantum Learning in different hybrid architectures.

Hob


Arryn Diaz
    Seemingly a story of a mysterious robot called Hob, this comic book is in reality a much more sophisticated construction of post-humanism and Singularity threads.This book was self-published by the author in limited edition and is considered out of print.

Introduction to Artificial Intelligence and Expert Systems


Dan W. Patterson
    It illustrates the knowledge-system approach and emphasises the relevant use of such knowledge in specific systems. A considerable portion of the text is devoted to the subject of knowledge representation, including methods of dealing with uncertain, incomplete and vague knowledge (e.g. methods related to nonmonotonic logics and commonsense reasoning).The book is divided into five parts related to a detailed analysis of knowledge: Introduction to Artificial Intelligence, Knowledge Representation, Knowledge Organisation and Manipulation, Perception, Communi-cation and Expert Systems and Knowledge Acquisition. Table of Contents Preface. PART 1: INTRODUCTION TO ARTIFICIAL INTELLIGENCE_Overview of Artificial Intelligence. Knowledge: General Concepts. LISP and Other AI Programming Languages. PART 2: KNOWLEDGE REPRESENTATION_Formalized Symbolic Logics. Dealing with Inconsistencies and Uncertainties. Probabilistic Reasoning. Structured Knowledge: Graphs, Frames, and Related Structures. Object-Oriented Representations. PART 3: KNOWLEDGE ORGANIZATION AND MANIPULATION_Search and Control Strategies. Matching Techniques. Knowledge Organization and Management. PART 4: PERCEPTION, COMMUNICATION, AND EXPERT SYSTEMS_Natural Language Processing. Pattern Recognition. Visual Image Understanding. Expert Systems Architectures. PART 5: KNOWLEDGE ACQUISITION_General Concepts in Knowledge Acquisition. Early Work in Machine Learning. Learning by Induction. Examples of Other Inductive Learners. Analogical and Explanation-Based Learning. References. Index.

Polyglot(): NPC_REVOLUTION


D. Richardson
    A world of fantasy and magic. A world that is a game.NPCs and players all insist she is an NPC, a part of the world. A part of the code of the game. A part of the fantasy to entertain the players. She rejects the idea, for her memories can't just be lies. Could they?Alex sets out to establish herself in the sandbox fantasy world, to find her identity, and to weather the storm between the coming players and the inhabitants of the new world.

Probabilistic Programming & Bayesian Methods for Hackers


Cameron Davidson-Pilon
    An intro to Bayesian methods and probabilistic programming from a computation/understanding-first, mathematics-second point of view.http://camdavidsonpilon.github.io/Pro...

The Handbook Of Artificial Intelligence, Volume 4


Avron Barr
    

Probabilistic Models of Cognition


Noah D. Goodman
    In particular, we examine how a broad range of empirical phenomena in cognitive science (including intuitive physics, concept learning, causal reasoning, social cognition, and language understanding) can be modeled using a functional probabilistic programming language called Church.

The Singularity is Nearer


Ray Kurzweil
    During the succeeding decade many of Kurzweil's predictions about technological advancements have been borne out, and their viability has become familiar to the public through such now commonplace concepts as AI, intelligent machines, and bioengineering.In this entirely new book Ray Kurzweil brings a fresh perspective to advances in the singularity--assessing the progress of many of his predictions and examining the novel advancements that, in the near future, will bring a revolution in knowledge and an expansion of human potential. Among the topics he discusses are rebuilding the world, atom by atom with devices like nanobots; radical life extension beyond the current age limit of 120; reinventing intelligence by expanding biological capacity with nonbiological intelligence in the cloud; how life is improving with declines in areas such as poverty and violence; and the growth of technologies such as renewable energy and 3-D printing, which can be applied to everything from clothes to building materials to growing human organs. He also considers the potential perils of biotechnology, nanotechnology, and artificial intelligence, including such topics of current controversy as how AI will impact unemployment and the safety of autonomous cars, and After Life technology, which will reanimate people who have passed away through a combination of data and DNA.

Grokking Deep Learning by Andrew Trask, Manning Publications


Andrew Trask
    Purchase of the print book ...Available here : readmeaway.com/download?i=1617293709            1617293709 Grokking Deep Learning PDF by Andrew TraskRead Grokking Deep Learning PDF from Manning Publications,Andrew TraskDownload Andrew Trask's PDF E-book Grokking Deep Learning

Theory Of Self Reproducing Automata


John von Neumann
    

Logic for Problem Solving


Robert Kowalski
    

Illuminating The Path: The Research And Development Agenda For Visual Analytics


James J. Thomas