- 1 Top 25 Rated Best Books On Artificial Intelligence To Read
- 1.1 Artificial Intelligence – A Modern Approach (3rd Edition) by Stuart Russell and Peter Norvig
- 1.2 Artificial Intelligence Engines: A Tutorial Introduction to the Mathematics of Deep Learning by James V Stone
- 1.3 Artificial Intelligence and Machine Learning by Chandra S.S.V
- 1.4 Artificial Intelligence Basics: A Non-Technical Introduction by Tom Taulli
- 1.5 Applied Artificial Intelligence: A Handbook for Business Leaders by Mariya Yao, Adelyn Zhou, Marlene Jia
- 1.6 Machine Learning for Dummie by John Paul Mueller and Luca Massaron
- 1.7 Make Your Own Neural Network by Tariq Rashid
- 1.8 The Hundred-Page Machine Learning Book by Andriy Burkov
- 1.9 Artificial Intelligence for Human by Jeff Heaton
- 1.10 Machine Learning for Beginners by Chris Sebastian
- 1.11 Homo Deus: A Short History of Tomorrow (nonfiction book)
- 1.12 Superintelligence: Paths, Dangers, Plans by Nick Bostrom
- 1.13 The Fourth Age: Smart Robots, Conscious Computers, and the Future of Humanity by Byron Reese
- 1.14 Life 3.0: Being Human in the Age of Artificial Intelligence by Max Tegmark
- 1.15 Do Androids Dream of Electric Sheep? by Philip K. Dick
- 1.16 Neuromancer by William Gibson
- 1.17 AI for Business and People by Alex Castrounis
- 1.18 Deep Learning by Aaron Courville, Ian Goodfellow, and Yoshua Bengio
- 1.19 Machine Learning Yearning by Andrew Ng
- 1.20 You Look Like a Thing and I Love You, Janelle Shane
- 1.21 How to Create a Mind by Ray Kurzweil
- 1.22 Analytics of Life: Making Sense of Artificial Intelligence, Machine Learning and Data Analytics by Meet Damlapinar
- 1.23 Our Final Invention by James Barrat
- 1.24 Human+ Machine: Reimagining Function in the Time of AI by Paul R. Daugherty and H. James Wilson
- 2 Conclusion
What’s AI (Artificial Intelligence)?
Artificial Intelligence is the discipline of research that simulates the processes of individual intellect on computer systems. These processes include the purchase of data, using them, and approximating decisions. The study subjects in AI comprise problem-solving, reasoning, planning, natural language, programming, and machine learning. Automation, Robotics and advanced computer applications and programs describe a livelihood in Artificial Intelligence. Fundamental foundations in maths, engineering, logic, and technology can go a very long way in kick-starting a livelihood in Artificial Intelligence.
Top 25 Rated Best Books On Artificial Intelligence To Read
Thanks to artificial intelligence, the planet as we know it might change indefinitely. Artificial intelligence is much more than just the buzzword of now. Although you have probably heard that the media discussion about robots taking our jobs along with the feasible utopia in which AI cures our problems, these prospective exaggerations could be damaging to forecasting the authentic technological future.
To provide a more in-depth understanding of AI, Pennbook‘ll be discussing with you twenty-five top Artificial Intelligence books which are shelf-worthy for 2020.
Artificial Intelligence – A Modern Approach (3rd Edition) by Stuart Russell and Peter Norvig
This edition covers the developments and changes in Artificial Intelligence because those covered in the previous edition of the publication in 2003. This publication covers the most recent advancement in AI in the subject of technical language recognition, machine translation, autonomous vehicles, and household robotics. Additionally, it covers the progress in areas like probabilistic reasoning, machine learning, and personal vision.
Artificial Intelligence Engines: A Tutorial Introduction to the Mathematics of Deep Learning by James V Stone
In this novel, key neural network learning algorithms are explained, followed by detailed mathematical investigations. Online computer programs collated from open source repositories give hands-on expertise of neural networks. It’s a perfect introduction into the algorithmic motors of modern-day artificial intelligence.
Artificial Intelligence and Machine Learning by Chandra S.S.V
This publication is mainly meant for postgraduate and undergraduate students of computer science and technology. This textbook covers the difference between the hard contexts of both Artificial Intelligence and Machine Learning. It provides the largest case studies and worked-out examples.
Along with Artificial Intelligence and Machine Learning, also, it covers various kinds of learning such as strengthened, supervised, unsupervised and statistical understanding. It features well-explained calculations and pseudo-codes for every topic, which makes this book quite helpful for students.
Artificial Intelligence Basics: A Non-Technical Introduction by Tom Taulli
This book gives you a basic grasp of Artificial Intelligence and its effect. It provides a non-technical introduction to important concepts like Machine Learning, Deep Learning, Natural Language Processing, Robotics and much more. Further, the author develops on the questions surrounding the upcoming effects of AI on facets which have social tendencies, integrity, authorities, business structures and everyday life.
Applied Artificial Intelligence: A Handbook for Business Leaders by Mariya Yao, Adelyn Zhou, Marlene Jia
Applied Artificial Intelligence is a practical guide for business leaders that are enthusiastic about leveraging machine intelligence to boost the productivity of the organizations and also the quality of life in their communities.
This publication concentrates on forcing concrete company decisions through programs of artificial intelligence and machine language. It’s among the most effective practical guides for business leaders interested in getting an actual value from the adoption of Machine Learning Technology.
Machine Learning for Dummie by John Paul Mueller and Luca Massaron
Machine Learning for Dummies provides an entry point for anybody seeking to acquire a foothold on Machine Learning. It covers all of the fundamental concepts and concepts of machine learning and how they apply to the actual world. It introduces remote programming in Python and R to technology machines to do data analysis and pattern-oriented jobs.
From little jobs and patterns, the viewers can extrapolate the viability of machine learning via internet ads, internet searches, fraud detection, etc. Authored by two information science specialists, this Artificial Intelligence novel makes it effortless for any layman to comprehend and execute machine learning effortlessly.
Make Your Own Neural Network by Tariq Rashid
Among those publications on artificial intelligence that provides its subscribers with a step-by-step journey through the Math of Neural Networks. It begins with very simple thoughts and slowly builds up a comprehension of how neural systems operate. Using Python language, it motivates its readers to construct their neural networks.
The publication is broken up into three components. The first element deals with the different mathematical ideas underlying the neural networks. Component 2 is sensible where subscribers have educated Python and are invited to make their neural networks. The next part provides a glimpse into the mysterious head of a neural network. Additionally, it guides the reader to acquire the codes functioning on a Raspberry Pi.
The Hundred-Page Machine Learning Book by Andriy Burkov
Andriy Burkov “The Hundred-Page Machine Learning Books” is considered by many industry experts as the best book on machine learning. For novices, it provides a comprehensive introduction to the essentials of machine learning. For seasoned professionals, it gives practical recommendations in the author’s rich experience in the area of AI.
The publication covers all effective approaches to machine learning. They vary from classical linear and logistic regression to new support vector machines, fostering, Deep Learning, and random forests. This book is ideal for those novices who wish to become knowledgeable about the maths behind machine learning algorithms.
Artificial Intelligence for Human by Jeff Heaton
This book helps its readers receive an overview and comprehension of AI algorithms. It’s supposed to educate AI for people who don’t have an extensive mathematical background. The readers will need to have just a basic understanding of computer programming and college algebra.
Fundamental AI algorithms like linear regression, clustering, dimensionality, and space metrics are covered in depth. The calculations are explained using numerical calculations that the readers can execute themselves and through intriguing examples and use cases.
Machine Learning for Beginners by Chris Sebastian
According to its name, Machine Learning for Beginners is intended for complete beginners. It outlines the background of the early days of machine learning about exactly what it’s become now. It clarifies how large data is very important to machine learning and the way that programmers use it to create learning algorithms. Concepts like AI, neural networks, swarm intelligence, etc., are explained in detail.
This Artificial Intelligence publication provides easy examples for the reader to comprehend the complex mathematics and probability statistics inherent machine learning. Additionally, it provides real-world situations of machine learning algorithms that are creating our lives better.
Homo Deus: A Short History of Tomorrow (nonfiction book)
After publishing the best-seller Sapiens, that explains the growth of humanity through the ages from apes into super-intelligent beings, Yuav Noah Harari (a historian, philosopher, and a professor at the Department of History in the University of Jerusalem) continues his hunt into the long run.
In his book Deus, he asserts that humankind will boost his efforts to attain absolute happiness, immortality and God-like abilities which may lead to various potential futures. Will humans eliminate control of machines? Will the guy be worshipped as God?
Nevertheless, the most important idea throughout the novel is the fact that it is going to end in uncoupling our intellect from emotions. Harari dives deep to philosophical problems like consciousness, individual emotions, individualism so if you’d prefer small philosophical thinking and questioning, be sure to read this publication.
Superintelligence: Paths, Dangers, Plans by Nick Bostrom
Superintelligence from Prof. Nick Bostrom is your publication on Artificial Intelligence security. Bostrom supposes how we could make Artificial Intelligence far superior to what we might even believe and what dangers this entails. He believes in illustrations of how things could go wrong and when superintelligence can replace us as the dominant life form on Earth.
One thing that stood out to me personally was that the parallelization of people with gorillas. If the destiny of gorillas relies more on people compared to themselves, could this mean that the destiny of people will rely more on AI than on our species? Another Fantastic philosophical publication on AI that raises more questions than it answers (which how it ought to be)
The Fourth Age: Smart Robots, Conscious Computers, and the Future of Humanity by Byron Reese
This intriguing book asserts that AI will have huge consequences for the human race, to the extent it will redefine what it means to be human. As a desktop, Reese sets from the past three ages in which technology has reshaped humankind and places up AI and robotics since the fourth largest era of transformation. To put it differently, it is a gripping (and amazingly optimistic) account of how we got where we are now, and the way we ought to approach the new era that is upon us.
Life 3.0: Being Human in the Age of Artificial Intelligence by Max Tegmark
Among Barack Obama’s treasured novels of 2018 and called Novel of the Year by the Times and The Daily Telegraph, this highly commended book more than lives up to the hype.
Inside, Tegmark, who’s a physicist and cosmologist, sets out to different AI truths in reality in an approachable and playful manner. Impressively, he manages to ask some very challenging questions and topics (How do we make a more prosperous world through automation? How do we protect AI systems from malicious and hacking use?) Without being overly high-brow or dumbing down – without telling the reader exactly what to believe.
Do Androids Dream of Electric Sheep? by Philip K. Dick
Originally published in 1968, Do Androids Dream of Electric Sheep? Is a publication by NY Times best-selling writer Philip K. Dick. Set in the wake of an apocalyptic nuclear war, the book paints a grim picture of what might happen to humankind if animal species have been wiped from the face of the planet.
Observing a war, a few people today escape Mars, but solitude motivates them to fulfil their new homeworld with AI replicas of birds, cats, sheep, cows, as well as individual robots. In an ironic twist, the government decides to prohibit these life-like robots which move into hiding in plain sight. It requires the prowess of Rick Deckard along with other bounty hunters to catch and destroy them at a well-crafted experience that matches out compellingly.
Neuromancer by William Gibson
With the manner AI is changing every aspect of individual life, you would be amazed to learn this science fiction thriller was published over a half decades past. Neuromancer is among the most acclaimed fiction books in the cyberpunk class and will be the first work to have clinched all three of the greatest awards given to science fiction functions: the Hugo Award, the Philip K. Dick Award, and the Nebula Award.
William Gibson’s debut fiction book, this magical name follows a former statistics executive called Henry Dorsett Case. After being found guilty of theft, the ex-data leader is given a second opportunity to explore cyberspace from the mysterious Armitage provided that he uses his abilities to combine the two strongest artificial intelligence-Wintermute and Neuromancer.
This publication provides an adrenaline-packed ride with storyline heaves. It spins as Case tries to conquer cyber law authorities and double-crossing representatives to attain his mission before the toxin takes off his ability to get cyberspace.
AI for Business and People by Alex Castrounis
This is only one of the very exciting business-related publications on artificial intelligence I’ve ever read. Period. As the business world becomes more consumer-driven, it is increasingly important that company leaders and executives possess a comprehension of machine learning and AI to integrate a coherent strategy for AI using their existing operations and layout a well-honed strategy for future advancements.
AI for Individuals and Company is the best publication for executives, managers, CEOs, and other non-technical leaders that are keen on utilizing artificial intelligence inside their companies. If you discover that science on AI is somewhat out of touch for non-technical people, this book is specially written for you. That is because it simplifies the subject and gives the clearest explanations of such an intricate idea.
Deep Learning by Aaron Courville, Ian Goodfellow, and Yoshua Bengio
Deep Learning by topic specialists Aaron Courville, Ian Goodfellow, and Yoshua Bengio is, undoubtedly, among the most enlightening and educational textbooks on AI. It mostly tackles the heart of this artificial intelligence field: profound learning. The book also investigates the nitty-gritty of machine learning. Unexpectedly, the writers have made these two very technical issues approachable for the reasonably informed layman whilst nevertheless being information-heavy.
Of note: The text and thoughts lean towards the technical aspect so that this book is possibly not for everybody. It would help if you had a little mathematical heritage to take full benefit of it. It could easily pass for a grad-level textbook, and you need to treat it as such. Nevertheless, people who have some history in this region will find plenty of profound learning insights.
Machine Learning Yearning by Andrew Ng
If you have got something for how-to guides and novels written in a cookbook-style, afterwards, Machine Learning Yearning from Andrew Ng ought to be among your must-have review tools for studying all subjects AI. A fantastic read for AI engineers and non-tech people alike, it provides wide-ranging coverage of machine learning theories and the way the technology has been used in AI-backed solutions.
As you may expect from a specialist at the forefront of machine learning, the book is presented in an extremely logical purchase. Surprisingly, it apes the vital things, processes, and compromises that being engineers and information scientists follow when implementing machine learning projects. This arrangement is what makes this a special publication.
You Look Like a Thing and I Love You, Janelle Shane
This publication uses animations and funny pop-culture experiments to check in the minds of these calculations that run our planet, which makes AI and Machine Learning equally entertaining and accessible. It was printed in November 2019.
The writer delivers the responses to each AI question you have ever requested and a few you haven’t. In this bright, frequently humorous introduction to the fascinating science of the time, Shane reveals these programs understand, neglect and accommodate and the way they reflect the very best and worst of humankind.
How to Create a Mind by Ray Kurzweil
The way to make a Head is the key to human thought shown. Inside this, Ray Kurzweil provides a provocative exploration of reverse-engineering the mind to make more smart machines. Additionally, he clarifies the consequences of our growing intelligence on the planet’s most pressing problems.
He wholeheartedly examines emotional and ethical intelligence as well as the roots of consciousness. Building from those basic concepts, he brings implications concerning our inevitable merging using smart technology.
Analytics of Life: Making Sense of Artificial Intelligence, Machine Learning and Data Analytics by Meet Damlapinar
If you’d like less philosophy and nuts and bolts on your research of AI, Mert Damlapinar has you covered with a manager-and-entrepreneur social breakdown of this area because it applies to large business, small business, and our everyday lives.
Damlapinar takes the dire forecasts of the effect of AI on the blue-collar workforce and extends them into the white-collar workforce, while at precisely the same time offering sunny forecasts for the future of their information analytics sector.
Analytics of Life is mandatory reading for men and women that wish to place their livelihood trajectories for a part of AI as opposed to a casualty.
Our Final Invention by James Barrat
In this book James Barrat (a documentary filmmaker for National Geographic, Discovery, PBS and much more ) distinguished Artificial Intelligence as humankind’s closing creation. It certainly exposes the dangers that might emerge out of General Artificial Intelligence; it suggests that superintelligence doesn’t necessarily indicate benevolence, and it outlines the very last decades of study on possible AI threads. Plus it will so notion extensive research and thorough interviews with men and women within the area.
Our closing Invention may have a somewhat pessimistic tone, and it may give you a feeling of despair, but that is why it is a fantastic book. It compels you to consider our potential, to attempt to discover new techniques to protect against everything from occurring. Social consciousness in its very best.
Human+ Machine: Reimagining Function in the Time of AI by Paul R. Daugherty and H. James Wilson
Accenture leaders Paul R. Daugherty and H. James Wilson utilize their expertise to show how businesses use AI to drive innovation and boost profitability. The way AI certainly transforms all company processes from customer support and innovations to productivity and workplace culture.
There is a significant range of quality reads concerning Artificial Intelligence. We do expect these implied books can assist you at least have a glimpse of this huge world this technological progress has been growing through the years.
Have fun studying!
Last update on 2020-10-22 / Affiliate links / Images from Amazon Product Advertising API