Python machine learning
by Sebastian Raschka · first published 2015
45% recommend45% neutral9% critical
Why HN recommends it
A hands-on, practical introduction to machine learning using Python. It focuses on applied skills and working code, suiting learners who prefer building over heavy theory.
Summarised by Claude from recommending comments
Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data -- its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of pre
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…cool stuff these days. It's still a great book, but I'd instead recommend a path that focuses on machine learning: - The Master Algorithm: made for a general audience, gives you a lay of the land - Python Machine Learning by Sebastian Raschka: gives you practical skills using python, scikit-learn, numpy, jupyter notebooks, pandas etc. From zero to kaggle in 4 chapters, goes deeper after that. Also goes into enough theory…
on “Ask HN: Best books on AI?” ↗…(https://smile.amazon.com/Introduction-Probability-Chapman-St...) * Stanford EE263: Introduction to Linear Dynamical Systems (http://ee263.stanford.edu/) Beginner: * Andrew Ng's class (http://cs229.stanford.edu) * Python Machine Learning (https://smile.amazon.com/Python-Machine-Learning-Sebastian-R...) * An Introduction to Statistical Learning (https://smile.amazon.com/Introduction-Statistical-Learning-A...) Intermediate: * Pattern…
on “Machine Learning for Software Engineers” ↗…background so ESL was interesting to go through. But I am more of a practical person, and I found ISL to be more suited for me when it came down to working on my project and supporting my choices. # Python Machine Learning Really great hands-on book ! Sebastian Raschka manages well to guide you through all steps of a ML project data: pre-processing, feature engineering, model selection... - all the steps are defined and…
on “A Junior Data Scientist Bookshelf (including Free Versions and HN Discussions)” ↗Would you recommend it? Which book would you recommend, a book with practical approach, comprehensive and readable for latest developments in dl? Some other recommendations include "Python Machine Learning" by Sebastian Raschka and Vahid Mirjalili "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" by Aurélien Géron
on “Ask: Is d2l.AI better book for latest deep learning?” ↗It's weird how mixed quality their books are, and how many overlapping books they have. From Packt I like Sebastian Raschka's books on Python Machine Learning. Other than that from time to time they do have some good "recipes", but hardly any of their books seems worth reading cover to cover.
on “50 Algorithms Every Programmer Should Know (Second Edition)” ↗Sebastian is also the author of “Python Machine Learning” https://www.amazon.com/dp/1789955750/
on “Intro to Deep Learning” ↗probably this https://www.amazon.ca/Python-Machine-Learning-Sebastian-Rasc...
on “Machine Learning from scratch: Bare bones implementations in Python” ↗More great Jupyter Notebooks in the AI field: 1) 16 notebooks from the book "Python Machine Learning" by Raschka & Mirjalili https://github.com/rasbt/python-machine-learning-book-2nd-ed... 2) Linear Regression, Logistic Regression, Random Forests, and k-Means Clustering notebooks by Nitin Borwankar https://github.com/nborwankar/LearnDataScience…
on “Reinforcement Learning Jupyter Notebooks” ↗…Python for Data Science came out in October 2017 - that one focuses on Pandas, numpy and Jupyter notebooks, reasonably good introduction to those libraries. The second edition of Sebastian Raschka's Python Machine Learning came out 2017 too - that one focuses more on scikit-learn and tensorflow, have only heard good things but haven't read much in it.
on “Ask HN: CS and programming books of 2017” ↗…Illuminated by Tim Roughgarden (https://algorithmsilluminated.org/). Great set of books, but poor quality, sadly. All printed on demand. Ditto with Sebastian Raschka's (early) books from Packt Publishing (Python Machine Learning). Great content, but poor printing (very low contrast, etc). This is not a debate on ebooks vs paper books, or PDF vs something else. It's about quality of printed books. I paid $$$ for Kevin Murphy's…
on “The enshittification of Amazon paperback books” ↗Going through: * Faust - Johann Wolfgang von Goethe * How To Read a Book - Mortimer J. Adler * Python Machine Learning 2nd Edition - Sebastian Raschka * Economics 19e - Samuelson/Nordhaus Next in line: * The Sleepwalkers - Hermann Broch * The Will to Power - Friedrich Nietzsche * Oxford Handbook of Business and Government…
on “Ask HN: 2018 Summer Reading List?” ↗