Data science from scratch
by Joel Grus · first published 2015
67% recommend30% neutral3% critical
Why HN recommends it
Gentle, concise introduction that builds core data science and machine learning algorithms in plain Python with minimal library use, so readers see how the pieces work; suits beginners who want to code along.
Summarised by Claude from recommending comments
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If you enjoy these kinds of explanations, "Data Science from Scratch" by Joel Grus explains many machine learning algorithms and has you implement simple versions of them in Python as you read along. It also covers linear regression and I wonder if that book is where the…
on “Linear Regression” ↗…science? I working through this book, which I do like: https://www.amazon.com/Data-Science-Scratch-Principles-Pytho... I’m rewriting the examples in Swift to help me learn: https://github.com/melling/data-science-from-scratch-swift Something with a little more theory might be good. Lots of the questions seem to require more theoretical knowledge.
on “Data Science Interview Questions” ↗You might like the book 'data science from scratch' by Joel Grus. He uses Python without ML libraries and explains clearly what's going on.
on “Google's Free Deep Learning Course” ↗I agree. I'd start with something like Joel Grus's Data Science From Scratch to get a handle on the basics in Python (or whatever the R equivalent is, I'm not familiar with R books). I do however find myself more and more wishing I knew data science-specific Unix commands, and…
on “Learn the basics of data science with these books” ↗I like the book "Data Science from Scratch" (2019) by Joel Grus, now in its 2nd edition, which implements algorithms in Python. But I wish the author used Numpy and implemented his own array classes, which I think is taking "from scratch" too…
on “Nothing but NumPy:Understanding and Creating Binary Classification NNs” ↗Maths.... Seriously how good is your calculus and statistics? Joel Grus book 'Data science from scratch' might be a start.
on “Ask HN: What do you want to learn in 2017?” ↗…of 5 coming out next week) - Practical Deep Learning for Coders Parts 1 & 2 - Book: Hands-on machine learning with TF and SKLearn (Aurelion Geron) If you want a really gentle path, I'd start with 'Data Science from Scratch' by Joel Grus. If you want to start at the deep end, buy the Deep Learning Book by Goodfellow et al. They review the relevant math at the beginning, but it's work to go through it. Perhaps if you recently…
on “Tech Giants Are Paying Huge Salaries for Scarce AI Talent” ↗…friends and colleagues struggle with some specific popular books. Sometimes its OK not to like the way someone writes even if they're really smart and super famous. My two favorite applied ones are * Data science from scratch because it's one of the most concise and logical expositions of most ML algorithms in simple python that you'll remember and be able to reproduce from scratch if need be https://www.amazon.com/Data-Science-Scratch-Principles-Pytho...…
on “Model-Based Machine Learning Book” ↗…read this yet, but just from Jake Vanderplas' reputation, I think it's probably worth If you want some more recs, my two favorites are Chris Albon's Machine Learning with Python Cookbook and Joel Grus' Data Science from Scratch: First Principles with Python
on “Python Data Science Handbook: Full Text in Jupyter Notebooks” ↗Data Science From Scratch By Joel Grus is my favorite book and it is the best for those people who doesn't know about Data Science
on “Best Data Science Books According to the Experts” ↗For your specific problem (avoiding the use of libraries that do too much of the work), two sources I found useful: - Data Science from Scratch, by Joel Grus - The first 5 deeplearning.ai courses (whose exercises relied only on numpy IIRC)
on “Ask HN: Those learning about neural networks, what do you find most difficult?” ↗…where you want to go. If you want to learn Python libraries like Tensorflow and Pytorch, Keras, and the like... there are many books for that. "Deep Learning with Python", by François Chollet.[4][5] "Data Science from Scratch: First Principles with Python", by Joel Grus.[6][7] There are the fast.ai courses on https://fast.ai and also have a book titled: "Deep Learning for Coders with Fastai and PyTorch: AI Applications Without…
on “Ask HN: What are the next steps I should take after finishing ML on coursera?” ↗I am currently reading "Data Science from Scratch" and feel this relates here. The book is nicely showing the principles of machine learning by showing how all the blocks are build. (We can program along as we read.) Also: My kid is too young for this,…
on “Build Your Own Artificial Neural Network” ↗The book should add a subtitle "Includes 116 line implementation of an in memory database" https://github.com/joelgrus/data-science-from-scratch/blob/m... +90 line implementation of neural networks, wow that is some beautiful code
on “Data Science from Scratch: First Principles with Python” ↗You can try "Data Science from Scratch" [0] to get some taste. It uses Python to teach essentials of data science, and ML altorithms. The code quality is very good, and there is an introduction to Statistics, Maths and Python to start. Then…
on “Ask HN: How do I go about learning machine learning?” ↗