learning_info

Links to future useful info I find and want to save for later.

Challenges:

[https://github.com/karan/Projects]

[https://news.ycombinator.com/item?id=15787023]

[https://github.com/tuvtran/project-based-learning/blob/master/README.md#python] - Project-based learning

[https://web.eecs.utk.edu/~azh/blog/challengingprojects.html] - Projects every programmer should try

Data Science:

[http://p.migdal.pl/2016/03/15/data-science-intro-for-math-phys-background.html#python]

[https://news.ycombinator.com/item?id=15127672] - Python Data Science Handbook

[https://www.dataquest.io/blog/making-538-plots/]

[https://github.com/cs109/2018-cs109b]

[http://data8.org/] - Data 8

[https://www.inferentialthinking.com/chapters/07/Visualization] - Data 8 Textbook so far...

[https://j253.github.io/blog/fun-with-nfl-stats.html] - Fun with NFL Stats

[https://mlwhiz.com/blog/2018/12/07/connected_components/] - Graph Theory in Data Science

[https://www.dataquest.io/blog/math-in-data-science/] - Maths in Data Science

[https://news.ycombinator.com/item?id=21158487] - Streamlit library

Numpy

[https://news.ycombinator.com/item?id=16473482]

Machine Learning:

[https://www.analyticsvidhya.com/blog/2017/05/pydata-amsterdam-2017-machine-learning-deep-learning-data-science/]

[http://imanmalik.com/cs/2017/06/05/neural-style.html] [https://github.com/indrajithi/mgc-django]

[https://sadanand-singh.github.io/posts/treebasedmodels/#.WXT8Kli2pUw.hackernews]

[https://news.ycombinator.com/item?id=14998352] - HN Free ML/AI Resources

[https://github.com/aymericdamien/TensorFlow-Examples/tree/master/]

[https://github.com/yufengg/widendeep]

[https://github.com/amygdala/tensorflow-workshop/tree/master/workshop_sections/wide_n_deep]

[https://www.youtube.com/playlist?list=PLIivdWyY5sqJxnwJhe3etaK7utrBiPBQ2]

[https://news.ycombinator.com/item?id=16167620]

[https://news.ycombinator.com/item?id=16247109]

[http://mlreference.com/spacy] - Spacy NLP

[https://medium.com/huggingface/100-times-faster-natural-language-processing-in-python-ee32033bdced] - Spacy X100 speedup

[https://medium.com/@karamanbk/39-machine-learning-resources-that-will-help-you-in-every-essential-step-b2696515ed9] - 39 Resources (medium.com)

[https://www.pyimagesearch.com/2018/06/18/face-recognition-with-opencv-python-and-deep-learning/] - ML and Open CV face recognition.

[http://explained.ai/matrix-calculus/index.html] - Maths for Deep Learning

[https://thomas-tanay.github.io/post--L2-regularization/] - A new angle on L2 regularisation.

[https://medium.com/@hiromi_suenaga/deep-learning-2-part-1-lesson-1-602f73869197] Notes for Fast.ai

[https://www.zerotosingularity.com/blog/fast-ai-part-1-course-1-annotated-notes/] Notes for Fast.ai

[https://developers.google.com/machine-learning/guides/] - Google ML Guides

[http://blog.petersobot.com/machine-learning-for-drummers] - Drum Sample recognition using ML

[https://mlcourse.ai/] - Machine Learning Course

[https://github.com/open-source-for-science/TensorFlow-Course] - TensorFlow course

[https://towardsdatascience.com/the-cold-start-problem-how-to-build-your-machine-learning-portfolio-6718b4ae83e9] - Building an ML portfolio

[https://github.com/trekhleb/homemade-machine-learning/blob/master/README.md] - ML Algorithms in Jupyter

[https://github.com/machinelearningmindset/machine-learning-course] - ML Course (github)

[https://github.com/keras-team/keras-tuner] - Keras tuner (Hyperparameters)

[https://iq.opengenus.org/face-aging-cgan-keras/] - Face aging using Keras

[https://yugeten.github.io/posts/2019/09/GP/] - Gaussian Processes

[https://ranvir.xyz/blog/svm-support-vector-machines-in-machine-learning/] - SVM Intro for ML

Python 3

[https://github.com/arogozhnikov/python3_with_pleasure]

[http://treyhunner.com/2018/10/asterisks-in-python-what-they-are-and-how-to-use-them/] - * and ** operators

Programming Style:

[https://henrikwarne.com/2018/03/13/exercises-in-programming-style/]

[http://treyhunner.com/2018/09/stop-writing-lambda-expressions/] - Lambda Expressions

[https://lwn.net/Articles/787800/] - inheritance vs composition

Books:

[http://shop.oreilly.com/product/9780596516130.do]

[http://www.deeplearningbook.org/]

[http://interactivepython.org/runestone/static/pythonds/index.html]

[http://chimera.labs.oreilly.com/books/1234000001813/index.html]

Links:

[https://news.ycombinator.com/item?id=14277039]

[https://blog.insightdatascience.com/using-deep-learning-to-reconstruct-high-resolution-audio-29deee8b7ccd]

[https://magenta.tensorflow.org/nsynth-fastgen]

[https://magenta.tensorflow.org/performance-rnn]

[http://lucumr.pocoo.org/2015/11/18/pythons-hidden-re-gems/]

[https://medium.com/@kacawi/python-for-finance-algorithmic-trading-60fdfb9bb20d]

Maths for CS:

[https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-042j-mathematics-for-computer-science-fall-2010/readings/]

[https://news.ycombinator.com/item?id=18939913] - Self study maths

[https://github.com/MikeInnes/diff-zoo] - Differentiation for hackers

[https://github.com/llSourcell/learn_math_fast] - Learn Maths Fast

Calculus:

[https://ocw.mit.edu/resources/res-18-006-calculus-revisited-single-variable-calculus-fall-2010/index.htm]

[https://ocw.mit.edu/resources/res-18-008-calculus-revisited-complex-variables-differential-equations-and-linear-algebra-fall-2011/index.htm]

[https://ocw.mit.edu/resources/res-18-007-calculus-revisited-multivariable-calculus-fall-2011/index.htm]

CS:

[https://mindweb.network/board/computer-science-a-full-bachelor-curriculum]

[https://github.com/jwasham/coding-interview-university]

[https://github.com/ossu/computer-science] - OSSU CS Curriculum

[https://news.ycombinator.com/item?id=20729252] - Books for CS HN Thread

[https://skerritt.blog/big-o/] - Big O notation with Python Examples

[https://teachyourselfcs.com/] - Teach Yourself CS

Everything:

[https://unsupervisedmethods.com/my-curated-list-of-ai-and-machine-learning-resources-from-around-the-web-9a97823b8524]

[https://chrisalbon.com/]

Cryptocurrency:

[https://blog.patricktriest.com/analyzing-cryptocurrencies-python/?utm_source=hackernews]

[https://news.ycombinator.com/item?id=15063469]

Finance:

[https://www.datacamp.com/community/tutorials/finance-python-trading]

[https://github.com/cantaro86/Financial-Models-Numerical-Methods] - Jupyter notebook collection

[https://python.quantecon.org/] - Quant Econ

[https://www.tradientblog.com/2019/11/lessons-learned-building-an-ml-trading-system-that-turned-5k-into-200k/] - Making $200k

Music

[https://rpiai.com/piano/] - Music AI

[https://news.ycombinator.com/item?id=17632999] - Music Pi

[https://towardsdatascience.com/making-music-when-simple-probabilities-outperform-deep-learning-75f4ee1b8e69] - DL vs probabilities

[https://github.com/deezer/spleeter] - Splitting audio into stems using ML

[https://nolannicholson.com/looper.html] - Seamlessly looping Music

Sudoku:

[http://norvig.com/sudoku.html]

Regex:

[https://blog.patricktriest.com/you-should-learn-regex/]

Maths:

Calculus Differential Equations Number Theory Real Analysis Discrete Mathematics

[http://robjlow.blogspot.co.uk/2017/06/what-is-this-thing-called-i.html]

[http://people.math.gatech.edu/~cain/textbooks/onlinebooks.html]

[https://www.amazon.com/dp/0992001005/noBSguide]

[https://news.ycombinator.com/item?id=15116379] - HN maths for AI/ML

[https://news.ycombinator.com/item?id=14581273] - HN Georgia Tech free maths textbooks

[https://plus.maths.org/content/unveiling-mandelbrot-set]

[https://news.ycombinator.com/item?id=15146746] - IBM Maths of Machine Learning

[http://acko.net/blog/how-to-fold-a-julia-fractal/]

[https://news.ycombinator.com/item?id=17664084] - Maths for ML

[https://news.ycombinator.com/item?id=17920650] - Differential Equations course

[http://joshua.smcvt.edu/linearalgebra/] - Free linear algebra textbook

[https://vankessel.io/blog/2019/01/06/visualizing-complex-functions] - Visualising Complex functions

[https://thonyc.wordpress.com/2019/10/16/calculus-for-the-curious/] - Calculus for the Curious

[https://www.neilwithdata.com/mathematics-self-learner] - Maths for the self-learner

[https://betterexplained.com/articles/linear-algebra-guide/] - Linear Algebra guide

Bayesian Statistics:

[https://news.ycombinator.com/item?id=15732926] - Think Bayes - Bayesian Statistics Made Simple

[https://medium.com/@benpshaver/a-zero-math-introduction-to-markov-chain-monte-carlo-methods-dcba889e0c50]

Learning:

[https://recurse.henrystanley.com/post/better/]

[https://news.ycombinator.com/item?id=17706776]

[https://news.ycombinator.com/item?id=17616937] - learning sites/games etc

[https://news.ycombinator.com/item?id=17892796] - how to learn difficult things

Git:

[https://rogerdudler.github.io/git-guide/] - Git command guide

[https://learngitbranching.js.org/] - Learn Git branching

[https://bitbucket.org/BitPusher16/dotfiles/raw/49a01d929dcaebcca68bbb1859b4ac1aea93b073/refs/git/git_examples.sh] - Git commands in one script

[https://github.blog/2015-06-08-how-to-undo-almost-anything-with-git/] How to do almost anything with Git

Background Jobs in Flask:

[https://blog.miguelgrinberg.com/post/the-flask-mega-tutorial-part-xxii-background-jobs]

SQL

[https://news.ycombinator.com/item?id=17690780] - SQL discussion

[https://news.ycombinator.com/item?id=17905666] - SQL interactive learning book

Databases

[http://webcache.googleusercontent.com/search?q=cache:z-c0s5-AdZ8J:coding-geek.com/how-databases-work/+&cd=12&hl=en&ct=clnk] - how relational databases work

Pandas

[http://pbpython.com/pandas-pivot-table-explained.html] - Pivot Tables

[https://kanoki.org/2019/09/16/dataframe-visualization-with-pandas-plot/] - Data Visualisation with Pandas

Algorithms

[https://visualgo.net/en] - Visual Algorithms

[https://bradfieldcs.com/algos/] - Practical Algorithms and Data Structures

[https://adrianmejia.com/blog/2018/04/04/how-you-can-change-the-world-learning-data-structures-algorithms-free-online-course-tutorial/#.W8dYeheQiu0.hackernews] - Data Structures and Algorithms (DSA) for Beginners

[https://news.ycombinator.com/item?id=18443311] - Infinite City generation

[https://runestone.academy/runestone/static/pythonds/index.html] - Problem Solving with Algorithms

UI

[https://github.com/dddomodossola/remi] - Remote UI

[https://build-system.fman.io/pyqt5-tutorial] - PyQT5 Tutorial

Jupyter Notebooks:

[https://florianwilhelm.info/2018/11/working_efficiently_with_jupyter_lab/] - Working Efficiently with Jupyter Notebooks

[https://github.com/hemanta212/blogger-cli] - Jupyter to blog

Vector Graphics:

[https://zulko.github.io/blog/2014/09/20/vector-animations-with-python/] - Gizeh library

[https://news.ycombinator.com/item?id=18919599] - learning GIT

Visualisation:

[https://www.machinelearningplus.com/plots/top-50-matplotlib-visualizations-the-master-plots-python/] - Top 50 plots

[https://www.labri.fr/perso/nrougier/python-opengl/#python-opengl-for-scientific-visualization] - Python and OpenGL Viz

React:

[https://news.ycombinator.com/item?id=19050509] - learn React fundamentals

Django:

[https://news.ycombinator.com/item?id=19542975] - pandas/jupyter comment

[http://shibel.blot.im/django-keeping-logic-out-of-templates-and-views] - keeping logic out of templates

NLP:

[https://course.spacy.io/] - SpaCy course

OCR:

[https://nanonets.com/blog/ocr-with-tesseract/] - Ocr with pytesseract

Hacking

[https://pwn.college/modules/suid] - Pwn College

Debugging and Logging

[https://martinheinz.dev/blog/24] - Debugging and logging with Python

JavaScript

[https://jvns.ca/blog/2020/06/19/a-little-bit-of-plain-javascript-can-do-a-lot/] - A little bit of JS can do a lot

Libraries

[https://github.com/kotartemiy/pygooglenews] - PyGoogle News - Google News Reader