An-Introduction-to-Statistical-Learning
ISLR-python
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An-Introduction-to-Statistical-Learning | ISLR-python | |
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2 | 10 | |
2,285 | 4,192 | |
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Jupyter Notebook | Jupyter Notebook | |
- | MIT License |
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An-Introduction-to-Statistical-Learning
- Can you recommend a Python textbook to replace "An Introduction to Statistical Learning with Applications in R", Witten, J. et. al. [E]
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Weekly Developer Roundup #21 - Sun Nov 08 2020
hardikkamboj/An-Introduction-to-Statistical-Learning (Jupyter Notebook): This repository contains the exercises and its solution contained in the book An Introduction to Statistical Learning in python.
ISLR-python
- How is this for a Data Analysis roadmap?
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DATA SCIENTIST ROADMAP
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
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[E] Please recommend statistics books for a beginner for data science.
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
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Have you found it impeding that the exercises in Intro to Statistical learning are in R?
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
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ESL vs ISLR books?
Here or here for the Python versions of ISLR.
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Low Level Books or Courses
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
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Looking for resources to get better at statistics
People have also recreated the examples in Python if that is your preferred language.
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I want to learn machine learning and I want to make small projects in the future. Where do I start? Any tips and advice?
ISLR Code in Python
- Help with An Introduction to Statistical Learning: Figure 1.3
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Maths for Deep Learning (mainly computer vision)
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).
What are some alternatives?
winapps - Run Windows apps such as Microsoft Office/Adobe in Linux (Ubuntu/Fedora) and GNOME/KDE as if they were a part of the native OS, including Nautilus integration.
ISL-python - Porting the R code in ISL to python. Labs and exercises
pifuhd - High-Resolution 3D Human Digitization from A Single Image.
ISLR.jl - JuliaLang version of "An Introduction to Statistical Learning: With Applications in R"
Sharing_ISL_python - An Introduction to Statistical Learning with Applications in PYTHON
ISLR-but-python - This repository contains labs rewritten in Python for the book An Introduction to Statistical Learning with Applications in R by James, Witten, Hastie, Tibshirani (2013)
youtube-dl-gui - A cross platform front-end GUI of the popular youtube-dl written in wxPython.
PythonDataScienceHandbook - Python Data Science Handbook: full text in Jupyter Notebooks
datascience-template - Data science project template
AI-Hacktoberfest - Welcome to the Hacktoberfest Challenge for Artificial Intelligence / Machine Learning ! Today we will be assessing your skills to Predict Forest Fire Areas given its various parameters!
yt-dlc - media downloader and library for various sites.
the-elements-of-statistical-learning - My notes and codes (jupyter notebooks) for the "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani and Jerome Friedman