Machine Learning Cheat Sheet download for Linux

This is the Linux app named Machine Learning Cheat Sheet whose latest release can be downloaded as machine-learning-cheat-sheetsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.

 
 

Download and run online this app named Machine Learning Cheat Sheet with OnWorks for free.

Sundin ang mga tagubiling ito upang patakbuhin ang app na ito:

- 1. Na-download ang application na ito sa iyong PC.

- 2. Ipasok sa aming file manager https://www.onworks.net/myfiles.php?username=XXXXX kasama ang username na gusto mo.

- 3. I-upload ang application na ito sa naturang filemanager.

- 4. Simulan ang OnWorks Linux online o Windows online emulator o MACOS online emulator mula sa website na ito.

- 5. Mula sa OnWorks Linux OS na kasisimula mo pa lang, pumunta sa aming file manager https://www.onworks.net/myfiles.php?username=XXXX gamit ang username na gusto mo.

- 6. I-download ang application, i-install ito at patakbuhin ito.

MGA SCREENSHOT:


Machine Learning Cheat Sheet


DESCRIPTION:

This repository is a visually rich and well-organized “cheat sheet” summarizing core machine learning concepts, algorithms, formulas, and best practices. It includes summaries of supervised and unsupervised learning methods, model evaluation metrics (accuracy, precision, recall, ROC/AUC), overfitting/underfitting, regularization (L1/L2), cross-validation, feature engineering techniques, and perhaps tips for hyperparameter tuning. Each section is presented concisely, often with diagrams, formula snippets, and short explanatory notes to serve as quick reference for students, practitioners, or interview prep. The repository is ideal for those who want a compact, at-a-glance reminder of ML fundamentals without diving back into textbooks. Because the cheat sheet is meant to be portable and broadly useful, it is format-friendly (often in Markdown, PDF, or image formats) and easy to include in learning workflow or slides.



Mga tampok

  • Compact summary of core supervised and unsupervised algorithms
  • Key formulas and metrics (loss functions, ROC/AUC, confusion matrix, regularization)
  • Visual diagrams illustrating model behavior or tradeoffs
  • Feature engineering, validation, and hyperparameter tuning tips
  • Community contributions and versioning for updates
  • Multi-format availability (Markdown / PDF / image) for portability



Kategorya

Algorithm

This is an application that can also be fetched from https://sourceforge.net/projects/machine-learning-cheat.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.



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