├── ML Cheat Sheets ├── Keras.pdf ├── Numpy.pdf ├── Pandas.pdf ├── PySpark.pdf ├── Seaborn.pdf ├── ggplot2.pdf ├── ML chart.jpeg ├── Matplotlib.pdf ├── PySpark_RDD.pdf ├── PySpark_SQL.pdf ├── Tensorflow.pdf ├── Scikit-Learn.pdf ├── Keras Cheat Sheet.png ├── Numpy Cheatsheet.webp ├── Pandas Cheatsheet.webp ├── Scipy Cheatsheet.webp ├── Neural Network Cells.pdf ├── Neural Network Graphs.pdf ├── Neural Networks Zoo.pdf ├── PySpark Cheatsheet.webp ├── SciPy-Linear Algebra.pdf ├── Tensorflow Cheatsheet.png ├── Matplotlib Cheatsheet.webp ├── Scikit-Learn Cheatsheet.png ├── ML Cheatsheets (combined).pdf ├── Scikit-learn cheat sheet.png ├── LangChain_Cheat_Sheet_KDnuggets.pdf ├── Qualitative and Quantitative.jpeg ├── top machine learning algorithms.png ├── Large Language Model Cheat Sheet.pdf ├── Twitter recommendation algorithm.jpeg ├── ChatGPT Cheat Sheet - How ChatGPT works.pdf ├── Bard_for_Data_Science_Cheat_Sheet_KDnuggets.pdf ├── Machine_Learning_with_ChatGPT_Cheat_Sheet_KDnuggets.pdf 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2023 Nhi Yen 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Machine Learning Cheatsheets 2 | 3 | ![Author](https://img.shields.io/badge/Author-Nhi%20Yen-brightgreen) 4 | [![Medium](https://img.shields.io/badge/Medium-Follow%20Me-blue)](https://medium.com/@yennhi95zz) 5 | [![GitHub](https://img.shields.io/badge/GitHub-Follow%20Me-lightgrey)](https://github.com/yennhi95zz) 6 | [![Kaggle](https://img.shields.io/badge/Kaggle-Follow%20Me-orange)](https://www.kaggle.com/nhiyen) 7 | [![LinkedIn](https://img.shields.io/badge/LinkedIn-Connect%20with%20Me-informational)](https://www.linkedin.com/in/yennhi95zz/) 8 | 9 | Welcome to the Machine Learning Cheatsheets repository! This collection of cheatsheets is designed to help you quickly reference key concepts, algorithms, and libraries in the field of Machine Learning. Whether you're a beginner looking for a quick overview or an experienced practitioner in need of a refresher, these cheatsheets can be a valuable resource. 10 | 11 | ## Cheatsheets 12 | 13 | Below are the cheatsheets currently available in this repository: 14 | 15 | 1. [Scikit-Learn Cheatsheet](https://scikit-learn.org/stable/tutorial/machine_learning_map/index.html): A comprehensive reference for Scikit-Learn, a popular Machine Learning library in Python. 16 | 17 | 2. [TensorFlow Cheatsheet](https://www.tensorflow.org/guide/cheatsheet): A quick reference for TensorFlow, a powerful open-source Machine Learning framework. 18 | 19 | 3. [PyTorch Cheatsheet](https://pytorch.org/tutorials/beginner/ptcheat.html): A cheatsheet for PyTorch, a popular deep learning framework. 20 | 21 | 4. [Matplotlib Cheatsheet](https://github.com/matplotlib/cheatsheets): Useful for creating data visualizations in Machine Learning projects. 22 | 23 | 5. [NumPy Cheatsheet](https://github.com/rougier/numpy-100): A fundamental library for scientific computing in Python, often used in Machine Learning. 24 | 25 | 6. [Pandas Cheatsheet](https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf): Helpful for data manipulation and analysis, commonly used in data preprocessing for Machine Learning. 26 | 27 | 7. [Keras Cheatsheet](https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Keras_Cheat_Sheet_Python.pdf): Useful for high-level neural network tasks, often used in conjunction with TensorFlow. 28 | 29 | 8. [Machine Learning Algorithms Cheat Sheet](https://www.datacamp.com/cheat-sheet/machine-learning-cheat-sheet): A comprehensive cheat sheet of Machine Learning algorithms. 30 | 31 | 9. [Machine Learning Math Cheat Sheet](https://medium.com/machine-learning-in-practice/cheat-sheet-of-machine-learning-and-python-and-math-cheat-sheets-a4afe4e791b6): A cheat sheet covering essential math concepts for Machine Learning. 32 | 33 | 10. [Machine Learning Interview Cheat Sheet](https://medium.com/swlh/cheat-sheets-for-machine-learning-interview-topics-51c2bc2bab4f): A cheat sheet to help you prepare for Machine Learning interviews. 34 | 35 | 11. [Linear Regression Cheat Sheet](https://thomasttam.medium.com/linear-regression-comprehensive-cheat-sheet-with-examples-a5e701d397f8): A comprehensive cheat sheet for Linear Regression. 36 | 37 | 12. [Logistic Regression Cheat Sheet](https://ml-cheatsheet.readthedocs.io/en/latest/logistic_regression.html): A reference for Logistic Regression with examples. 38 | 39 | 13. [Decision Tree Cheat Sheet](https://towardsdatascience.com/cheat-sheet-decision-trees-terminology-c37ee6cb2d2e): An overview of Decision Trees and their terminology. 40 | 41 | 14. [Support Vector Machine Cheat Sheet](https://medium.com/analytics-vidhya/machine-learning-cheat-sheat-support-vectors-machines-8abb9c350804): A cheat sheet for Support Vector Machines (SVM). 42 | 43 | 15. [Random Forest Cheat Sheet](https://medium.com/analytics-vidhya/machine-learning-models-cheatsheet-7885b33ca44f): An overview of Random Forests and their usage. 44 | 45 | 16. [Gradient Boosting Machine Cheat Sheet](https://medium.com/@WenxinZhang98/ml-models-comparison-890d782c6e32): A reference for Gradient Boosting Machines. 46 | 47 | 17. [K-Means Clustering Cheat Sheet](https://towardsdatascience.com/clustering-cheat-sheet-dcf72259abb6): A cheat sheet for K-Means Clustering. 48 | 49 | 18. [Hierarchical Clustering Cheat Sheet](https://towardsdatascience.com/clustering-cheat-sheet-dcf72259abb6): An overview of Hierarchical Clustering. 50 | 51 | 19. [Principal Component Analysis Cheat Sheet](https://cheatography.com/dganesh/cheat-sheets/principal-component-analysis/): A reference for Principal Component Analysis (PCA). 52 | 53 | 20. [Singular Value Decomposition Cheat Sheet](https://www.studocu.com/de/document/technische-universitat-munchen/control-theory-mse/cheat-sheet-control-theory/7353208): An overview of Singular Value Decomposition (SVD). 54 | 55 | 21. [T-Distributed Stochastic Neighbor Embedding Cheat Sheet](https://towardsdatascience.com/t-distributed-stochastic-neighbor-embedding-t-sne-bb60ff109561): A cheat sheet for t-SNE. 56 | 57 | To learn more, check out the **ML Cheat Sheets** folder in the main branch. 58 | 59 | ## Contributing 60 | 61 | We encourage contributions to expand the collection of cheatsheets. If you'd like to add more cheatsheets to this repository, follow these steps: 62 | 63 | 1. Fork this repository. 64 | 65 | 2. Create a new markdown (.md) or Jupyter Notebook (.ipynb) file for the new cheatsheet in the appropriate category within the `Cheatsheets` directory. 66 | 67 | 3. Ensure that the cheatsheet is well-structured and includes clear explanations, code snippets, and relevant references. 68 | 69 | 4. Update this README.md file to include a link to the new cheatsheet in the "Cheatsheets" section. 70 | 71 | 5. Submit a pull request with your changes, and we'll review and merge it. 72 | 73 | Please make sure to provide proper attribution and adhere to any licensing requirements if you use content from external sources. 74 | 75 | ## Star History 76 | 77 | [![Star History Chart](https://api.star-history.com/svg?repos=yennhi95zz/machine-learning-cheatsheets&type=Date)](https://star-history.com/#yennhi95zz/machine-learning-cheatsheets&Date) 78 | 79 | 80 | 81 | ## License 82 | 83 | This repository is licensed under the [MIT License](LICENSE), which means you are free to use, modify, and distribute the content for both personal and commercial purposes while providing attribution. 84 | 85 | We hope you find these cheatsheets helpful in your Machine Learning journey. Feel free to reach out with suggestions, feedback, or requests for new cheatsheets. Happy learning! 86 | 87 | --------------------------------------------------------------------------------