shervinea / stanford-cme-106-probability-and-statistics
VIP cheatsheets for Stanford's CME 106 Probability and Statistics for Engineers
☆715Updated 4 years ago
Alternatives and similar repositories for stanford-cme-106-probability-and-statistics:
Users that are interested in stanford-cme-106-probability-and-statistics are comparing it to the libraries listed below
- VIP cheatsheets for Stanford's CME 102 Ordinary Differential Equations for Engineers☆240Updated 4 years ago
- A series of Python Jupyter notebooks that help you better understand "The Elements of Statistical Learning" book☆872Updated 3 years ago
- Translation of VIP cheatsheets for Machine Learning Deep Learning, and Artificial Intelligence☆904Updated 2 years ago
- Study guides for MIT's 15.003 Data Science Tools☆1,818Updated 4 years ago
- The motive behind Creating this repo is to feel the fear of mathematics and do what ever you want to do in Machine Learning , Deep Learni…☆675Updated 2 years ago
- General statistics, mathematical programming, and numerical/scientific computing scripts and notebooks in Python☆913Updated 2 years ago
- This is a companion to the ‘Mathematical Foundations’ section of the book, Mathematics for Machine Learning by Marc Deisenroth, Aldo Fais…☆268Updated 4 years ago
- Cracking the Data Science Interview☆342Updated 5 years ago
- FREE ML Courses from Top Universities in CS☆249Updated 10 months ago
- VIP cheatsheets for Stanford's CS 221 Artificial Intelligence☆2,673Updated 5 years ago
- An ongoing list of pandas quirks☆954Updated last year
- An Introduction to Statistical Learning with Applications in PYTHON☆540Updated 3 years ago
- My notes and codes (jupyter notebooks) for the "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani and Jerome Frie…☆408Updated 3 years ago
- Machine learning and deep learning resources☆526Updated this week
- Python Feature Engineering Cookbook, published by Packt☆473Updated 2 years ago
- The textbook Computational and Inferential Thinking: The Foundations of Data Science☆826Updated 6 months ago
- COMS W4995 Applied Machine Learning - Spring 20☆245Updated 3 years ago
- Code and files to go along with CS329s machine learning model deployment tutorial.☆605Updated 2 years ago
- ☆342Updated 4 years ago
- Data science interview questions with answers. Not ideally (yet)☆1,607Updated 2 years ago
- Jupyter Notebooks for Springer book "Python for Probability, Statistics, and Machine Learning"☆762Updated 2 years ago
- Machine Learning Open Source University☆881Updated 2 months ago
- Compilation of resources for aspiring data scientists☆2,056Updated 9 months ago
- Porting the R code in ISL to python. Labs and exercises☆194Updated 2 years ago
- A roadmap for those looking to start or expand a career in the data community☆292Updated 10 months ago
- ☆306Updated 2 years ago
- A repository to prepare you for your machine learning interview, involving most of the questions asked by all the tech giants and local c…☆480Updated 7 months ago
- Curated list of publicly accessible machine learning engineering courses from CalTech, Columbia, Berkeley, MIT, and Stanford.☆453Updated last year
- AI-related tutorials. Access any of them for free → https://towardsai.net/editorial☆1,005Updated 10 months ago
- Full Stack Deep Learning Online Course☆894Updated 3 years ago