10 Essential Cheat Sheets for Data Scientist

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Cheat sheets are a great way to access knowledge. What makes a good cheat sheet is picking the most fundamental material. By visiting these sheets, you’ll master the tools of data science.

1. NumPy: A cheat sheet for NumPy, a Python library used for working with arrays and matrices. It includes a list of commonly used functions and their syntax.
2. Pandas: A cheat sheet for Pandas, a Python library used for data manipulation and analysis. It includes functions for importing data, selecting and filtering data, and data visualization.
3. Matplotlib: A cheat sheet for Matplotlib, a Python library used for data visualization. It includes a list of commonly used plotting functions and their syntax.
4. Seaborn: A cheat sheet for Seaborn, a Python library built on top of Matplotlib that provides additional functionality for data visualization. It includes functions for creating different types of plots and customizing their appearance.
5. Scikit-learn: A cheat sheet for Scikit-learn, a Python library used for machine learning. It includes functions for loading and preparing data, building and evaluating models, and data preprocessing.
6. Keras: A cheat sheet for Keras, a Python library used for building and training deep learning models. It includes functions for creating different types of layers and models, compiling models, and training models.
7. PyTorch: A cheat sheet for PyTorch, a Python library used for building and training deep learning models. It includes functions for creating different types of layers and models, defining loss functions, and training models.
8. SQL: A cheat sheet for SQL, a language used for managing and querying relational databases. It includes syntax for basic SQL commands such as SELECT, WHERE, and JOIN.
9. Regular expressions: A cheat sheet for regular expressions in Python, which are used for pattern matching and text processing. It includes a list of commonly used regular expression patterns and their syntax.
10. Git: A cheat sheet for Git, a version control system used for tracking changes to code. It includes commands for creating and managing branches, committing changes, and merging changes from different branches.

1. NumPy: https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Numpy_Python_Cheat_Sheet.pdf
2. Pandas: https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf
3. Matplotlib: https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Python_Matplotlib_Cheat_Sheet.pdf
4. Seaborn: https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Python_Seaborn_Cheat_Sheet.pdf
5. Scikit-learn: https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Scikit_Learn_Cheat_Sheet_Python.pdf
6. Keras: https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Keras_Cheat_Sheet_Python.pdf
7. PyTorch: https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Pytorch_Cheat_Sheet.pdf
8. SQL: https://cdn.sqltutorial.org/wp-content/uploads/2016/04/SQL-cheat-sheet.pdf
9. Regular expressions: https://www.debuggex.com/cheatsheet/regex/python
10. Git: https://education.github.com/git-cheat-sheet-education.pdf

Best of luck!