Ben Auffarth - Artificial Intelligence with Python Cookbook

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Ben Auffarth is a full-stack data scientist with more than 15 years of work experience. With a background and Ph.D. in computational and cognitive neuroscience, he has designed and conducted wet lab experiments on cell cultures, analyzed experiments with terabytes of data, run brain models on IBM supercomputers with up to 64k cores, built production systems processing hundreds of thousands of transactions per day, and trained neural networks on millions of text documents. He resides in West London with his family, where you might find him in a playground with his young son. He co-founded and is the former president of Data Science Speakers, London.

va barbosa is a software engineer in the Qiskit Community at IBM, focused on building open source tools and creating educational content for developers, researchers, students, and educators in the field of quantum computing. Previously, va was a developer advocate at the Center for Open-Source Data and AI Technologies where he assisted developers discover and make use of data science and machine learning technologies. He is fueled by his passion to help others and guided by his enthusiasm for open source technology.

Eyal Wirsansky is an Artificial Intelligence consultant and mentor, a senior software engineer, and a technology community leader. Eyal leads the Jacksonville (FL) Java User Group, hosts the Artificial Intelligence for Enterprise virtual user group, writes a developer-oriented Artificial Intelligence blog, and often speaks about topics related to Artificial Intelligence, Machine Learning and Genetic Algorithms. Eyal is the author of the book Hands-On Genetic Algorithms with Python.

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Artificial Intelligence (AI) is the field concerned with automating tasks in a way that exhibits some form of intelligence to human spectators. This apparent intelligence could be similar to human intelligence, or simply some insightful action a machine or program surprises us with. Since our understanding of the world improves along with our tools, our expectations of what would surprise us or strike us as intelligent are continuously being raised. Rodney Brooks, a well-known researcher in the field of AI, expressed this effect (often referred to as the AI effect ):

(Cited from Kahn, Jennifer (March 2002). It's Alive, in Wired, 10 (30): https://www.wired.com/2002/03/everywhere/ )

AI has made huge strides, especially over the last few years with the arrival of powerful hardware, such as Graphics Processing Units ( GPUs) and now Tensor Processing Units ( TPUs ) , that can facilitate more powerful models, such as deep learning models with hundreds of thousands, millions, or even billions of parameters. These models perform better and better on benchmarks, often reaching human or even super-human levels. Excitingly for anyone involved in the field, some of these models, trained for many thousands of hours that would be worth hundreds of thousands of dollars if run on