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You're reading from  Machine Learning for Time-Series with Python

Product typeBook
Published inOct 2021
PublisherPackt
ISBN-139781801819626
Edition1st Edition
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Ben Auffarth
Ben Auffarth
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Ben Auffarth

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 and thousands of transactions per day, and trained language models on a large corpus of text documents. He co-founded and is the former president of Data Science Speakers, London.
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Introduction to reinforcement learning

Reinforcement learning is one of the main paradigms in machine learning alongside supervised and unsupervised methods. A major distinction is that supervised or unsupervised methods are passive, responding to changes, whereas RL is actively changing the environment and seeking out new data. In fact, from a machine learning perspective, reinforcement learning algorithms can be viewed as alternating between finding good data and doing supervised learning on that data.

Computer programs based on reinforcement learning have been breaking through barriers. In a watershed moment for artificial intelligence, in March 2016, DeepMind's AlphaGo defeated the professional Go board game player Lee Sedol. Previously, the game of Go was considered to be a hallmark of human creativity and intelligence, too complex to be learned by a machine.

It has been argued that it is edging us closer toward Artificial General Intelligence (AGI). For example...

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Machine Learning for Time-Series with Python
Published in: Oct 2021Publisher: PacktISBN-13: 9781801819626

Author (1)

author image
Ben Auffarth

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 and thousands of transactions per day, and trained language models on a large corpus of text documents. He co-founded and is the former president of Data Science Speakers, London.
Read more about Ben Auffarth