ISLR-python VS PythonDataScienceHandbook

3) Then, work through the ISLR book: Book: https://www.statlearning.com/ Video: https://www.youtube.com/playlist?list=PLoROMvodv4rOzrYsAxzQyHb8n_RWNuS1e Jupyter Notebooks (Python version): https://github.com/JWarmenhoven/ISLR-python

Also, if you know you’re going to be using Python, you can find repos out there with the code converted from R to Python on Github. Ex: https://github.com/JWarmenhoven/ISLR-python

Lots of people redid the labs in Python if you really want Python instead, a quick google search gave me https://github.com/alexandrasouly/ISLR-but-python and https://github.com/JWarmenhoven/ISLR-python

Here or here for the Python versions of ISLR.

I don't think many people know this, but there's actually a very helpful Python Github repo to accompany the ISLR book (which uses R). Hope this helps :D

People have also recreated the examples in Python if that is your preferred language.

ISLR Code in Python

I am facing the same problem! I worked through the fastai tutorials for land classification purposes and felt there was a real gap between what I was doing in Python and what I actually understood. I found the fastai tutorials were a great start when followed by a math refresher like the introduction to statistical learning (ISLR) from Stanford. I know Stanford was changing its online class format on the Lagunita platform, but hopefully its still free and online. The profs wrote it in R, but here is a python wprkthrough. (https://github.com/JWarmenhoven/ISLR-python).

Python Data Science Handbook

Python Data Science Handbook — learn to use Python libraries such as NumPy, Pandas, Matplotlib, Scikit-Learn, and related tools to effectively store, manipulate, and gain insight from data

I don't know what tools you will be using but if you will be using Python you can start with Python Data Science Handbook by Jake VanderPlas and Data Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting DataData Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data which gives a very good outlook on the data science and big data frame work. PS: Jake's book is also available as jupyter notebooks so you can read and run the code at the same time.

Python Data Science Handbook by Jake VanderPlas (https://jakevdp.github.io/PythonDataScienceHandbook/)

Otherwise you can work through courses on Datacamp, Coursera, Udemy, etc, or check out this book for a more general non-spatial perspective.

7. Data Science Handbook Are you looking for a comprehensive guide to data science with Python? Look no further than the Data Science Handbook by Jake VanderPlas. This repository contains the entire book, which introduces essential tools and techniques used in data science, including IPython, NumPy, Pandas, Matplotlib, and Scikit-Learn. It’s a fantastic resource for anyone looking to deepen their understanding of data science concepts and best practices.

I can recommend https://jakevdp.github.io/PythonDataScienceHandbook/