What's the best book for someone who has experience with python at a basic level and want an indepth understanding of it? Looking to eventually get into data science/ML. Thanks
Python Learning
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official docs/specs
dont learn python plz learn julia instead fo sho'
I have to take a class in python anyway so I want to delve into it myself first
Fluente Python
>Looking to eventually get into data science/ML
Read and try to understand people's kaggle notebooks and what they're doing
...
I'll look into this
YT videos if you're new to programming. Docs if you know another language.
A Byte of Python
My life the picture.
I've got to sort myself now..
This. Python Cookbook as well maybe.
brb printing this out and putting it on my monitor
just type help() and there's a link to online documentation right at the top.
If you have basic understanding of python you're pretty much there.
Just watch a few of Raymond Hettinger's lectures and start getting hands-on experience. You'll learn by reading the docs
Cliffnotes version:
> use generators
> don't declare classes if you only init and get
> use logging
If you're into ML just get a coursera course in python.
>Looking to eventually get into data science/ML
Your time would be better spent on learning the basics of linear algebra, multivariable calculus, probability theory, and algorithmic analysis. You can learn python as you go.
damn
The O'reilly book with a rat in it. It's like 1.2k pages
>that feeling when somebody actually gives legit advice but words his post like a mouthbreathing retard so he gets ignored
I doubt you have actually used Julia
Udemy has data analysis and machine in python. Python is the easy part though
no idea
So much this. This applies to pretty much any new language. The "learn python the hard way" meme was getting nauseating.
This, or go on libgen.io and find an advanced python book
There's also a CMU intro compsci course with short video tutorials if you click on the lectures
kosbie.net
CMU also has their ML courses open
youtube.com
Or the reg intro
cs.cmu.edu
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Algorithm Design by Kleinberg and Tardos
Artificial Intelligence: A Modern Approach by Russell and Norvig
Introduction to Probability Theory by Hoel, Port, and Stone
Introduction to Stochastic Processes by Hoel, Port, and Stone
Probability and Statistics by DeGroot and Schervish
inference.phy.cam.ac.uk
Pattern Recognition and Machine Learning by Bishop
Bayesian Data Analysis by Gelman, Carlin, Stern, Dunson, Vehtari, and Rubin