Alternatives and similar repositories for cs189-su18

Users that are interested in cs189-su18 are comparing it to the libraries listed below

• GitYCC / machine-learning-papers-summary
  機器學習論文筆記
  ☆51Updated 4 years ago
• dhdepddl / Mining-Massive-Data-Sets
  Stanford CS246 Mining Massive Data Sets course HW
  ☆15Updated 8 years ago
• hduongtrong / ST210A
  Homework for STAT 210A - Berkeley
  ☆30Updated 11 years ago
• stappit / all-of-statistics
  Solutions to Wasserman's 'All of Statistics'.
  ☆104Updated 6 years ago
• kushagra06 / CS221_AI
  🥚 Stanford CS221: Artificial Intelligence: Principles and Techniques
  ☆84Updated 7 years ago
• kushagra06 / CS228_PGM
  🌀 Stanford CS 228 - Probabilistic Graphical Models
  ☆122Updated 7 years ago
• Hsins / NTU-Courses
  🎒 Materials (slides, handouts, homework, cheat sheets...) of the courses I took or audited at National Taiwan University.
  ☆42Updated 4 years ago
• MLaPP-Solution-Manual / Solutions-to-Machine-Learning-A-Probabilistic-Perspective-
  Solutions to "Machine Learning: A Probabilistic Perspective"
  ☆164Updated 4 years ago
• talwarabhimanyu / my-solutions-The-Elements-of-Statistical-Learning
  My solutions to problems of The Elements of Statistical Learning by Profs. Hastie, Tibshirani, and Friedman.
  ☆91Updated 6 years ago
• mlss-2019 / slides
  ☆260Updated 6 years ago
• joe-of-all-trades / deep-learning-cv
  Course Material for "Application of Deep Learning in Computer Vision"
  ☆97Updated 7 years ago
• dgkim5360 / the-elements-of-statistical-learning-notebooks
  Jupyter notebooks for summarizing and reproducing the textbook "The Elements of Statistical Learning" 2/E by Hastie, Tibshirani, and Frie…
  ☆296Updated 7 years ago
• cjlin1 / simpleNN
  ☆49Updated 4 years ago
• thtang / ML2017FALL
  Machine Learning (EE 5184) in NTU
  ☆68Updated 6 years ago
• ppaquay / Learning-from-Data-Solutions
  Repository of my solutions to the problems of "Learning from Data"
  ☆277Updated 5 years ago
• Dolores2333 / MATH5411
  All you need for MATH5411 Advanced Probability, 2020 Fall, HKUST, Lecturer BAO Zhigang.
  ☆56Updated 5 years ago
• orbxball / ML2017
  2017 Spring (105-2) -- Machine Learning
  ☆38Updated 4 years ago
• pecu / PyTorch_CSX
  PyTorch Taipei & NTU CS+X 讀書會
  ☆57Updated 7 years ago
• mlss-2019 / tutorials
  ☆275Updated 5 years ago
• 2wavetech / Probabilistic-Graphical-Model
  This repository contains my implementation of the programming assignments of Probabilistic Graphical Models delivered by Stanford Univers…
  ☆35Updated 8 years ago
• joyiswu / UCL-Deep-learning-ans-Reinforcement-learning
  Deep learning and Reinforcement learning lecture and course work
  ☆100Updated 7 years ago
• Zhenye-Na / advanced-deep-learning-and-reinforcement-learning-deepmind
  🎮 Advanced Deep Learning and Reinforcement Learning at UCL & DeepMind | YouTube videos 👉
  ☆156Updated 6 years ago
• WomenWhoCodeTaipei / DeepLearningwithPython
  Machine Learning and Data Science study group starting Sep'2018
  ☆38Updated 7 years ago
• snowdj / CS228_PGM
  🌀 Stanford CS 228 - Probabilistic Graphical Models
  ☆92Updated 7 years ago
• xbresson / CE7454_2019
  Deep learning course CE7454, 2019
  ☆191Updated 6 years ago
• shiernee / Advanced_ML
  ☆91Updated 2 years ago
• xbresson / CE7454_2018
  Deep learning course CE7454, 2018
  ☆79Updated 6 years ago
• sshkhr / Practical_RL
  My solutions to Yandex Practical Reinforcement Learning course in PyTorch and Tensorflow
  ☆53Updated 4 years ago
• ivannz / mlss2019-bayesian-deep-learning
  MLSS2019 Tutorial on Bayesian Deep Learning
  ☆93Updated 6 years ago
• dvklopfenstein / PrincetonAlgorithms
  Python implementations of selected Princeton Java Algorithms and Clients by Robert Sedgewick and Kevin Wayne
  ☆169Updated 8 months ago