PythonDataScienceHandbook
missing-semester
PythonDataScienceHandbook | missing-semester | |
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98 | 375 | |
41,593 | 4,708 | |
- | 1.2% | |
0.6 | 6.8 | |
18 days ago | 2 months ago | |
Jupyter Notebook | CSS | |
MIT License | GNU General Public License v3.0 or later |
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PythonDataScienceHandbook
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About Data analyst, data scientist and data engineer, resources and experiences
Python Data Science Handbook
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Where to learn data science with python??
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
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Book Recommendations
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.
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Other programing options?
Python Data Science Handbook by Jake VanderPlas (https://jakevdp.github.io/PythonDataScienceHandbook/)
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Pathways out of GIS?
Otherwise you can work through courses on Datacamp, Coursera, Udemy, etc, or check out this book for a more general non-spatial perspective.
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Mastering Data Science: Top 10 GitHub Repos You Need to Know
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.
- Help a lady out (career advice(
- Resources for Current DE Interested in Learning Data Science
- Good book or course to learn Python for someone who is fluent in R?
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Python equivalent to R's ecosystem of open source educational materials
I can recommend https://jakevdp.github.io/PythonDataScienceHandbook/
missing-semester
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Ask HN: I want to learn to use the terminal, where do I start
The missing semester of your cs education
https://missing.csail.mit.edu/
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Please advise, still struggling intensely
You mentioned having issues with accessory concepts so perhaps this might help: https://missing.csail.mit.edu/. There's also a chapter on git
- Curso del IPN
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CS2030S and CS2040S advice
https://missing.csail.mit.edu/ is a good way to pass the Dec-Jan break if you want to prep for CS2030S + some more general stuff.
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I cancelled my Replit subscription
Reflecting a little bit more I don't think it was replit's fault, per-say. But that change should have been made together with a larger adjustment to the program. Like adding a class/unit in the style of [the missing semester](https://missing.csail.mit.edu/) to make sure people came away with a good range of intuitions.
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Advice to a Novice Programmer
From MJD's post: I think CS curricula should have a class that focuses specifically on these issues, on the matter of how do you actually write software?
But they never do.
FWIW, MIT's "The Missing Semester of Your CS Education" attempts to deal with this lack, though, even there, it's an unofficial course taught between terms, during MIT's IAP -- Independent Activities Period[1] -- and not an actual CS course.
[0] https://missing.csail.mit.edu/
[1] https://en.wikipedia.org/wiki/Traditions_and_student_activit...
- School of SRE: Curriculum for onboarding non-traditional hires and new grads
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Advice / Resources from a "Seasoned Beginner"
Link to the "missing semester of your CS degree" course by MIT.
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MIT's Missing Semester Class: Beyond the CS Curriculum
Rightly called The Missing Semester (of Your CS Education), this class from MIT will teach you how to use some of the tools that are fundamental to the software engineering ecosystem. From shell scripting to the fundamentals of information security—spanning around 12 lectures—you can add a bunch of practical skills to your toolbox.
- ¿Recomendaciones sobre que aprender?
What are some alternatives?
django-livereload-server - Livereload functionality integrated with your Django development environment.
cs-topics - My personal curriculum covering basic CS topics. This might be useful for self-taught developers... A work in development! This might take a very long time to get finished!
Exercism - Scala Exercises - Crowd-sourced code mentorship. Practice having thoughtful conversations about code.
computer-science - :mortar_board: Path to a free self-taught education in Computer Science!
Serpent.AI - Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!
CS50x-2021 - 🎓 HarvardX: CS50 Introduction to Computer Science (CS50x)
lego-mindstorms - My LEGO MINDSTORMS projects (using set 51515 electronics)
vimrc - The ultimate Vim configuration (vimrc)
OSQuery - SQL powered operating system instrumentation, monitoring, and analytics.
javascript - JavaScript Style Guide
devdocs - API Documentation Browser
materials - Bonus materials, exercises, and example projects for our Python tutorials