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Machine Learning with Python

Machine Learning with Python

Principles and Practical Techniques
Parteek Bhatia , Thapar University, India
March 2023
Not yet published - available from March 2023
Adobe eBook Reader
9781009333603
$49.99
USD
Adobe eBook Reader
USD
Paperback

Machine learning has become a dominant problem-solving technique in the modern world, with applications ranging from search engines and social media to self-driving cars and artificial intelligence. This lucid textbook presents the theoretical foundations of machine learning algorithms, and then illustrates each concept with its detailed implementation in Python to allow beginners to effectively implement the principles in real-world applications. All major techniques, such as regression, classification, clustering, deep learning, and association mining, have been illustrated using step-by-step coding instructions to help inculcate a 'learning by doing' approach. The book has no prerequisites, and covers the subject from the ground up, including a detailed introductory chapter on the Python language. As such, it is going to be a valuable resource not only for students of computer science, but also for anyone looking for a foundation in the subject, as well as professionals looking for a ready reckoner.

  • Algorithms are explained in detail with examples with a step-by-step approach to make learning easy and simple, assuming no previously existing knowledge
  • GitHub resources that provide access to datasets, sample code, and examples have been included in each chapter
  • Advanced topics like Deep Learning, Convolutional Neural Networks, and Recurrent Neural Networks have been covered extensively
  • An online supplements package includes a solutions manual and lecture slides for instructors, and further online reading and a chapter-wise list of project ideas for students

Product details

March 2023
Adobe eBook Reader
9781009333603
0 pages
Not yet published - available from March 2023

Machine learning has become a dominant problem-solving technique in the modern world, with applications ranging from search engines and social media to self-driving cars and artificial intelligence. This lucid textbook presents the theoretical foundations of machine learning algorithms, and then illustrates each concept with its detailed implementation in Python to allow beginners to effectively implement the principles in real-world applications. All major techniques, such as regression, classification, clustering, deep learning, and association mining, have been illustrated using step-by-step coding instructions to help inculcate a 'learning by doing' approach. The book has no prerequisites, and covers the subject from the ground up, including a detailed introductory chapter on the Python language. As such, it is going to be a valuable resource not only for students of computer science, but also for anyone looking for a foundation in the subject, as well as professionals looking for a ready reckoner.