AI är vetenskap och teknik för att tillverka intelligenta maskiner, särskilt intelligenta datorprogram. Hela formen av AI är artificiell intelligens. Artificiell intelligens finns när en maskin har en kognitiv förmåga. Riktmärket för AI är den mänskliga nivån när det gäller resonemang, tal och vision.
Här är en sammanställd lista över de bästa AI-böckerna som bör ingå i alla nybörjare till avancerade datavetenskapslärares bibliotek.
1) Artificiell intelligens för dummies
Artificiell intelligens är en bok skriven av John Paul Mueller och Luca Massaron. Boken ger en tydlig introduktion till AI och hur den används idag.
Inuti denna bok får du en översikt över tekniken. Det talar också om de vanliga missuppfattningarna kring det. Boken utforskar användningen av AI i datorprogram, omfattning och historia för AI.
Kontrollera senaste pris och användarrecensioner på Amazon2) Skapa ditt eget neurala nätverk
Denna referensbok om artificiell intelligens är en steg-för-steg-resa genom matematiken i neurala nätverk och gör din egen med hjälp av Python-datorspråket.
Denna referensbok tar dig med på en rolig och orolig resa. Boken börjar med mycket enkla idéer och bygger gradvis upp en förståelse för hur neurala nätverk fungerar. I den här boken lär du dig att koda i Python och göra ditt neurala nätverk till att erbjuda professionellt utvecklade nätverk.
Kontrollera senaste pris och användarrecensioner på Amazon3) Superintelligens
Superintelligence är en idealisk referensbok skriven av Stuart Russell och Peter Norvig. Denna bok är den mest omfattande, uppdaterade introduktionen till AI-ämnes teori och praktik.
Den här AI-boken håller läsarna uppdaterade om den senaste tekniken, presenterar koncept på ett mer enhetligt sätt. Boken erbjuder också maskininlärning, djupinlärning, multi-agent-system för överlärning, robotik etc.
Kontrollera senaste pris och användarrecensioner på Amazon4) Artificiell intelligens: en modern strategi
Denna bok erbjuder en grundläggande konceptuell teori om artificiell intelligens. Det fungerar som ett komplett referensmaterial för nybörjare. Det hjälper studenter på grundutbildning eller forskarutbildningskurser i artificiell intelligens.
Denna utgåva ger dig detaljerad information om de förändringar som har ägt rum inom artificiell intelligens från den senaste utgåvan. Det finns många viktiga tillämpningar av AI-teknik som användning av praktisk taligenkänning, maskinöversättning, hushållsrobotar som förklaras detaljerat.
Kontrollera senaste pris och användarrecensioner på Amazon5) Artificiell intelligensmotorer: En självstudie Introduktion till matematik för djupt lärande
Artificial Intelligence Engines är en bok skriven av James V Stone. Boken förklarar hur AI-algoritmer, i form av djupa neurala nätverk. Det eliminerar snabbt den fördelen. Djupa neurala nätverk används för många affärsapplikationer som cancerdiagnos, objektigenkänning, taligenkänning, robotkontroll, schack, poker, etc.
I den här boken förklaras viktiga neurologiska nätverksinlärningsalgoritmer följt av detaljerade matematiska analyser.
Kontrollera senaste pris och användarrecensioner på Amazon6) Life 3.0: Att vara människa i en tid av artificiell intelligens
Life 3.0: Being Human in the Age of Artificial Intelligence är en bok skriven av Max Tegmark. Boken talar om ökningen av AI hur den har potential att förändra vår framtid mer än någon annan teknik.
Denna bok täcker också hela utbudet av synpunkter eller de mest kontroversiella frågorna. Den talar om betydelsen, medvetandet och de ultimata fysiska gränserna för livet i kosmos.
Kontrollera senaste pris och användarrecensioner på Amazon7) Maskininlärning för absoluta nybörjare
Machine Learning For Absolute Beginners är en bok skriven av Oliver Theobald. Boken täcker kapitel som Vad är maskininlärning, typer av maskininlärning, verktygslådan för maskininlärning, dataskrubbning av dina data, regressionsanalys. Boken täcker också kluster, supportvektormaskiner, artificiella neurala nätverk, bygga en modell i Python, etc. Den innehåller algoritmer som Cross-Validation, Ensemble Modeling, Grid Search, Feature Engineering och One-hot Encoding.
Kontrollera senaste pris och användarrecensioner på Amazon8) Deep Learning Illustrated
Deep Learning Illustrated is an AI book written by Jon Kohn, Grant Beyleveld, and Aglae Basens. This book talks about many powerful new artificial intelligence capabilities and algorithm performance. Deep Learning Illustrated and offers a complete introduction to the discipline's techniques.
This book can serve as a practical reference guide for developers, researchers, analysts, and students who want to apply it.
Check Latest Price and User Reviews on Amazon9) Predictive Analytics For Dummies
Predictive Analytics For Dummies is a book written by Anasse Bari, Mohamed Chaouchi, and Tommy Jung. With the help of this reference book, you will learn about the core of predictive analytics.
The book offers some common use cases to help you get started. It also covers details on modeling, k-means clustering. The book also provides tips on business goals and approaches.
Check Latest Price and User Reviews on Amazon10) Data Science from Scratch: First Principles with Python
Data Science from Scratch is a book written by Joel Gurus. This book helps you to learn math and statistics that is at the core of data science. You will also learn hacking skills you need to get started as a data scientist.
The books include topics like implement k-nearest neighbors, naïve bayes, linear and logistic regression, decision trees, and clustering models. You will also able to explore natural language processing, network analysis, etc.
Check Latest Price and User Reviews on Amazon11) Hands-On Machine Learning
Hands-On Machine Learning is a book written by Aurélien Géron. The book helps you gain an intuitive understanding of the concepts and tools for building intelligent systems.
This reference material also teaches you techniques, starting with simple linear regression and progressing to deep neural networks. In this book, you will also explore several training models, including support vector machines, decision trees, random forests, and ensemble methods. You can also learn techniques for training and scaling deep neural networks.
Check Latest Price and User Reviews on Amazon12) Applied Artificial Intelligence: A Handbook For Business Leaders
Applied Artificial Intelligence is a book written by Mariya Yao, Adelyn Zhou, and Marlene Jia. This book is a practical guide for business leaders who are passionate about leveraging machine intelligence. This helps you to enhance the productivity of their organizations and the incase the quality of life in their communities. The book also helps you to take business decisions through applications of AI and machine learning.
Check Latest Price and User Reviews on Amazon13) Prediction Machines: The Simple Economics of Artificial Intelligence
Prediction Machines is a book written by Ajay Agrawal, Joshua Gans, and Avi Goldfarb. The book talks about the heart of making decisions under uncertainty. It also explains how prediction tools increase productivity-- operating machines, handling documents, communicating with customers. In the end, the book discusses how better prediction creates opportunities for new business structures.
Check Latest Price and User Reviews on Amazon14) Human + Machine: Reimagining Work in the Age of AI
Human + Machine: Reimagining Work in the Age of AI is a book written by Paul R. Daugherty and H. James Wilson. The book talks about the essence of the AI paradigm, which helps you to shift is the transformation of all business processes inside a single organization.
The book explains how companies are using the new rules of AI to leap ahead on innovation. It also describes six entirely new types of hybrid human + machine roles that every company must develop.
Check Latest Price and User Reviews on Amazon15) Architects of Intelligence: The truth about AI from the people building it
Architects of Intelligence contain a series of in-depth, one-to-one interviews where the author, Martin Ford, reveals the truth behind these questions. He has given thoughts of the brightest minds in the Artificial Intelligence community.
This AI book helps collects the opinions of the luminaries of the AI business, Like Stuart Russell, Rodney Brooks, Demis Hassabis, and Yoshua Bengi. You should read this book to get in-depth knowledge and the future of the AI field.
Check Latest Price and User Reviews on Amazon16) Artificial Intelligence for Humans: Fundamental Algorithms
Artificial Intelligence for Humans is a book written by Jeff Heaton. In this AI book, you will learn about the basic Artificial Intelligence algorithms. Like dimensionality, clustering, error calculation, hill climbing, Nelder Mead, and linear regression.
This Artificial Intelligence book explains all algorithms using actual numeric calculations that you can perform yourself. Every chapter in this book includes a programming example. Examples are currently provided in Java, C#, Python, and C. Other languages planned.
Check Latest Price and User Reviews on Amazon17) HBR's 10 Must Reads on AI, Analytics, and the New Machine Age
HBR's 10 Must Reads on AI, Analytics, and the New Machine Age is a book written by Micheal E. Porter, Thomas H. Davenport, Paul Daugherty, H. James Wilson.
The book combed through hundreds of Harvard Business Review articles and selected the most important ones. This book helps you to understand various AI consent and how to adopt them.
In this book, you will learn data science, driven by artificial intelligence and machine learning. It also covers chapters about the blockchain and Augmented reality.
Check Latest Price and User Reviews on Amazon18) TensorFlow in 1 Day: Make your own Neural Network
TensorFlow is the most popular Deep Learning Library available in the market. It has a most authentic graph computations feature which helps you to visualize and designed neural network. This useful Machine learning book offers both convolutions as well as Recurrent Neural network.
Machine learning models supported by TensorFlow like Deep Learning Classification, Boston Tree, and wipe & deep layer methods are covered in the book. The book includes complete professional deep learnings practices with detailed examples.
Check Latest Price and User Reviews on Amazon19) Deep Learning (Adaptive Computation and Machine Learning series)
This deep learning book offers a mathematical and conceptual background, and relevant concepts in linear algebra, probability and information theory, and machine learning.
The book describes many important deep learning techniques widely used in industry, which includes regularization, optimization algorithms, sequence modeling. This book also offers research-related information like linear factor models, autoencoders, structured probabilistic models, the partition function, etc.
Check Latest Price and User Reviews on Amazon20) Python Machine Learning, 1st Edition
Python Machine Learning book gives you access to the world of predictive analytics. It helps you to learn the best practices and methods to improve and optimize machine learning systems and algorithms.
Wants to find out how to use Python? Then you should pick up Python Machine Learning. The book helps you to get started from scratch, or helps you to extend your data science knowledge.
Check Latest Price and User Reviews on Amazon21) Deep Learning with R
Deep Learning with R introduces you to a universe of deep learning using the Keras library and its R language interface. It is written for Python as Deep Learning with Python by Keras creator and Google.
The books help you set up your deep-learning environment. You can also practice your new skills with R-based applications in computer vision, natural language processing, and generative models. Moreover, to learn this course, you don't need any previous experience of machine learning or deep learning.
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