- https://github.com/r0f1/ml_checklist
- From Data to Viz
- Python Graph Gallery
- The Data Visualisation Catalogue
- Top 50 matplotlib Visualizations
- Financial Times Visual Vocabulary
- Engineering Statistics Handbook - EDA chapter
- [ru] https://habr.com/ru/post/468295/
- Data Viz Project
- https://www.analyticsvidhya.com/blog/2015/06/infographic-cheat-sheet-data-exploration-python/
- [ru] https://nagornyy.me/courses/data-science/intro-to-seaborn/
- https://infovis.fh-potsdam.de/tutorials/
- https://clauswilke.com/dataviz/ecdf-qq.html
Common
Geo
Time Series
- Book Feature Engineering for Machine Learning (Repo)
- Book Flexible Imputation of Missing Data (examples in R)
- Book Forecasting: Principles and Practice (examples in R)
- Book Applied Time Series Analysis for Fisheries and Environmental Sciences (examples in R)
- https://github.com/rob-med/awesome-TS-anomaly-detection
- https://christophm.github.io/interpretable-ml-book/
- https://github.com/jphall663/interpretable_machine_learning_with_python
- MLBox
- Auto Sklearn
- TPOT
- mljar-supervised
- H2O
- Auto Keras
- Google Cloud AutoML
- Uber Ludwig
- Voila
- Streamlit
- nteract - Open Jupyter Notebooks with doubleclick.
- papermill - Parameterize and execute Jupyter notebooks, tutorial
- nbdime - Diff two notebook files, Alternative GitHub App: ReviewNB.
- RISE - Turn Jupyter notebooks into presentations.
- pivottablejs - Drag n drop Pivot Tables and Charts for jupyter notebooks.
- jupyter-datatables - Interactive tables in Jupyter.
- debugger - Visual debugger for Jupyter.
- Python debugger (pdb) - blog post, video, cheatsheet
- General Jupyter Tricks
- Jupyter notebooks features
- https://github.com/ajcr/100-pandas-puzzles
- https://pandas.pydata.org/pandas-docs/stable/user_guide/10min.html
- https://github.com/guipsamora/pandas_exercises
- https://github.com/firmai/pandasvault
- https://github.com/jvns/pandas-cookbook
- https://www.kaggle.com/python10pm/pandas-100-tricks
- https://www.machinelearningplus.com/python/101-pandas-exercises-python/
- https://github.com/TomAugspurger/effective-pandas
- https://elitedatascience.com/python-cheat-sheet
- https://www.datacamp.com/community/tutorials/pandas-tutorial-dataframe-python
- https://nbviewer.jupyter.org/github/justmarkham/pandas-videos/blob/master/top_25_pandas_tricks.ipynb#18.-Aggregate-by-multiple-functions
- https://www.notion.so/Pandas-Tutorials-Articles-Videos-a19c806a31bb4b288a1909f0803fad5f
- https://pandas.pydata.org/pandas-docs/stable/user_guide/cookbook.html
- https://github.com/tdpetrou/Learn-Pandas
- https://github.com/tdpetrou/Minimally-Sufficient-Pandas
- https://github.com/rougier/numpy-100
- http://cs231n.github.io/python-numpy-tutorial/
- http://jalammar.github.io/visual-numpy/
- http://scipy-lectures.org/
- https://docs.scipy.org/doc/scipy/reference/stats.html
- https://seeing-theory.brown.edu/
- https://gallery.shinyapps.io/CLT_mean/
- https://gallery.shinyapps.io/dist_calc/
- https://setosa.io/#/
- https://distill.pub
- https://the-learning-machine.com/list-articles/machine-learning
- https://rpsychologist.com/
- https://github.com/PyTorchLightning/pytorch-lightning
- https://github.com/jettify/pytorch-optimizer
- https://github.com/lutzroeder/netron
- https://github.com/wandb/client
- http://playground.tensorflow.org
- https://www.cs.ryerson.ca/~aharley/vis/conv/
- https://github.com/Atcold/pytorch-Deep-Learning
- https://github.com/tensorflow/lucid/#activation-atlas-notebooks
- https://poloclub.github.io/cnn-explainer/
- https://distill.pub/2016/misread-tsne/
- https://sites.google.com/view/lauraepp/parameters
- https://python-data-science.readthedocs.io/
- http://martin.zinkevich.org/rules_of_ml/rules_of_ml.pdf
- https://paperswithcode.com/sota
- http://www.r2d3.us/visual-intro-to-machine-learning-part-1/
- http://www.r2d3.us/visual-intro-to-machine-learning-part-2/
- https://github.com/donnemartin/data-science-ipython-notebooks
- https://github.com/jvawdrey/cookiecutter-data-science
- https://github.com/graykode/nlp-roadmap
- https://github.com/donnemartin/data-science-ipython-notebooks
- [ru] https://ranalytics.github.io/data-mining/index.html
- http://rali.iro.umontreal.ca/rali/sites/default/files/publis/SokolovaLapalme-JIPM09.pdf
- https://explained.ai/
- https://gto76.github.io/python-cheatsheet/
- https://chrisalbon.com/
- https://github.com/EthicalML/awesome-production-machine-learning