├── Research_Papers ├── Topics_Index └── README.md /Research_Papers: -------------------------------------------------------------------------------- 1 | # This file presents an index of papers (organized by topic) which seem to be important and/or of interest in machine learning. 2 | -------------------------------------------------------------------------------- /Topics_Index: -------------------------------------------------------------------------------- 1 | # The following provides an index of topics in machine learning loosly ordered by discipline and subdiscipline accross categories. 2 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Hackers_Introduction_to_Machine_Learning 2 | A running collection of resources for people who want to get started in machine learning and data science 3 | 4 | ## Open Courseware: 5 | 6 | ### Mathematical Foundations: 7 | #### Linear Algebra 8 | Kahn Academy Linear Algebra Lectures: 9 | https://www.khanacademy.org/math/linear-algebra 10 | MIT OCW 18.06 with Gilbert Strang (Linear Algebra): 11 | https://www.youtube.com/watch?v=ZK3O402wf1c&list=PL49CF3715CB9EF31D 12 | #### Probability and Statistics 13 | Kahn Academy High School Statistics: 14 | https://www.khanacademy.org/math/probability#table-of-contents 15 | MIT OCW 6.041 Probability and Statistics: 16 | https://www.youtube.com/watch?v=j9WZyLZCBzs&list=PLQ3khvAsNhargDx0dG1cQXOrA2u3JsFKc 17 | https://www.youtube.com/watch?v=j9WZyLZCBzs&list=PLUl4u3cNGP60A3XMwZ5sep719_nh95qOe 18 | Harvard Statistics 110: Probability: 19 | https://www.youtube.com/playlist?list=PL2SOU6wwxB0uwwH80KTQ6ht66KWxbzTIo 20 | 21 | #### Deep Learning: 22 | Andrew Ng Coursera (A good place to start): 23 | https://www.coursera.org/learn/machine-learning 24 | 25 | Originally taught as CS229 on Youtube by Andrw Ng: 26 | https://www.youtube.com/watch?v=UzxYlbK2c7E&list=PLA89DCFA6ADACE599 27 | 28 | Nando de Freitas Oxford Lectures on Deep Learning (Introductory) 29 | https://www.youtube.com/watch?v=dV80NAlEins&list=PLE6Wd9FR--EfW8dtjAuPoTuPcqmOV53Fu 30 | 31 | #### Neural Networks by Geoffrey Hinton (Formerly Coursera) 32 | https://www.youtube.com/watch?v=cbeTc-Urqak&list=PLoRl3Ht4JOcdU872GhiYWf6jwrk_SNhz9 33 | 34 | #### Probabalistic Graphical Models (Daphne Kohler) 35 | https://www.youtube.com/watch?v=WPSQfOkb1M8&list=PL50E6E80E8525B59C 36 | 37 | #### Natural Language Processing Stanford (Formerly Coursera) 38 | https://www.youtube.com/watch?v=nfoudtpBV68&list=PL6397E4B26D00A269 39 | 40 | #### Statistical Learning Theory 41 | #### MIT Course 9.520 - Statistical Learning Theory and Applications 42 | Fall 2015: 43 | https://www.youtube.com/playlist?list=PLyGKBDfnk-iDj3FBd0Avr_dLbrU8VG73O 44 | Fall 2006: 45 | http://ocw.mit.edu/courses/brain-and-cognitive-sciences/9-520-statistical-learning-theory-and-applications-spring-2006/ 46 | 47 | #### More MIT OCW Statistical Learning Theory 48 | 18.465 Spring 2007: 49 | http://ocw.mit.edu/courses/mathematics/18-465-topics-in-statistics-statistical-learning-theory-spring-2007/ 50 | 51 | 52 | ### Job Boards, Community, News Aggregators: 53 | 54 | Kaggle: 55 | https://www.kaggle.com/ 56 | 57 | Data Tau: 58 | http://www.datatau.com/ 59 | 60 | Hacker News: 61 | https://news.ycombinator.com/ 62 | 63 | Glass Door: 64 | https://www.glassdoor.com/index.htm 65 | 66 | ### Implementation and Tutorials: 67 | 68 | Tensor Flow Playground: 69 | http://playground.tensorflow.org 70 | 71 | ConvNetJS: Deep learning in your web browser (Andrej Karpathy): 72 | http://cs.stanford.edu/people/karpathy/convnetjs/ 73 | 74 | Scikit-Learn: 75 | Jake Vanderplas PyCon 2015 Sckit-Learn Tutorial: 76 | https://www.youtube.com/watch?v=L7R4HUQ-eQ0 77 | 78 | Deep Learning: 79 | Theano: 80 | http://deeplearning.net/tutorial/ 81 | 82 | ### Blogs and Blog Posts: 83 | 84 | Andrej Karpathy: 85 | Blog: http://karpathy.github.io/ 86 | 87 | A Hacker's Guide to Neural Networks: http://karpathy.github.io/neuralnets/ 88 | 89 | ### Some Notable Names in Research: 90 | https://www.quora.com/Who-are-some-notable-machine-learning-researchers 91 | --------------------------------------------------------------------------------