“Perhaps the best test of a man’s intelligence is his capacity for making a summary” — Lytton Strachey
1. Introduction
Machine learning is an ever-growing field, there are numerous tools & techniques to remember. It is not possible for anyone to remember all these functions, operations and formulas for each of concept. That’s why we have cheat sheets and summaries. They help us access the most commonly needed reminders for making our Data Science journey fast and easy.
2. Basic Machine learning algorithms
2.1 Algorithm Summary
Source 1: machinelearningmastery.com/a-tour-of-machin..
Source 2: datacamp.com/cheat-sheet/machine-learning-c..
Source 3: docs.microsoft.com/en-us/azure/machine-lear..
source 4: cheatography.com/spriiprad/cheat-sheets/mac..
2.2 Algorithm Pro/Con
Source: blog.dataiku.com/machine-learning-explained..
3. Basic Machine learning algorithms Implementation
Source: analyticsvidhya.com/blog/2015/09/full-cheat..
3.1 Linear Regression
3.2 Logistic Regression
3.3 Decision Tree
3.4 Support Vector Machine(SVM)
3.5 Naive Bayes
3.6 k-Nearest Neighbours
3.7 k-Means
3.8 Random Forest
3.9 Dimensionality Reduction Algorithm
3.10 Gradient Boosting & ADA Boosting
4. Database
4.1 SQL
Source: sqltutorial.org/sql-cheat-sheet
4.2 MongoDB
Source: blog.codecentric.de/files/2012/12/MongoDB-C..
5. Data Manipulation
5.1 Numpy
Source 1:datacamp.com/cheat-sheet/numpy-cheat-sheet-..
Source 2:intellipaat.com/mediaFiles/2018/12/Python-N..
5.2 SciPy
Source 1: datacamp.com/cheat-sheet/scipy-cheat-sheet-..
Source 2: s3.amazonaws.com/assets.datacamp.com/blog_a..
5.3 Pandas
Source 1:datacamp-community-prod.s3.amazonaws.com/db..
Source 2:intellipaat.com/mediaFiles/2018/12/Python-P..
5.4 Data Wrangling
Source: pandas.pydata.org/Pandas_Cheat_Sheet.pdf
6. Data Visualization
6.1 Matplotlib
Source: s3.amazonaws.com/assets.datacamp.com/blog_a..
6.2 Seaborn
Source: s3.amazonaws.com/assets.datacamp.com/blog_a..
6.3 Folium
Source: andrewchallis.co.uk/articles/python-a-foliu..
7.Machine Learning, Deep Learning, Big Data
7.1 Scikit-Learn
Source 1: scikit-learn.org/stable/tutorial/machine_le..
Source 2 : s3.amazonaws.com/assets.datacamp.com/blog_a..
7.2 Keras
Source 1: raw.githubusercontent.com/rstudio/cheatshee..
Source 2:s3.amazonaws.com/assets.datacamp.com/blog_a..
7.3 Tensorflow
Source 1: becominghuman.ai/cheat-sheets-for-ai-neural..
Source 2 :cdn-images-1.medium.com/max/2000/1*dtOZSuYD..
7.4 PyTorch
Source 1: pytorch.org/tutorials/beginner/ptcheat.html
Source 2: blog.finxter.com/top-pytorch-cheat-sheets
7.5 PySpark
Source 1: datacamp.com/community/blog/pyspark-cheat-s..
Source 2: datacamp.com/community/blog/pyspark-sql-che..
8. Conclusion
Please feel free to add in your views and suggestions for the same and I promise to keep an eye on each of them and add them to the list above!
Till then.. Happy Learning!!
Cheers :)