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-====== Useful Links ======
-This page will contain links to helpful on-line material.
-===== Jobs in Machine Learning =====
-[[https://www.google.com/search?q=jobs+machine+learning+deep+learning&oq=jobs+machine+learning+deep+learning&aqs=chrome..69i57.4854j0j4&sourceid=chrome&ie=UTF-8&ibp=htl;jobs&sa=X&ved=0ahUKEwjSgrHjm7jZAhWH5oMKHVCFDtIQiYsCCC4oAA#fpstate=tldetail&htidocid=8goL71ReXwLp29yxAAAAAA%3D%3D&htivrt=jobs|ML jobs, a few near Fort Collins]]
-===== Recent News =====
-[[https://distill.pub/|Distill]], useful explanations of machine learning concepts.
-[[https://groups.google.com/g/ml-news?pli=1|ML News Google Group]]
-[[https://mailman.srv.cs.cmu.edu/mailman/listinfo/connectionists|Connectionists Mailing List]]
-[[https://towardsdatascience.com/|Towards Data Science, introductions and tutorials related to machine learning]]
-[[https://aitopics.org/class/AI-Alerts|AAAI AI-Alerts]]
-[[https://www.deeplearningweekly.com/|Deep Learning Weekly]]
-[[https://medium.com/topic/machine-learning|Medium: Machine Learning]]
-[[https://thegradient.pub/|The Gradient]]
-[[https://videos.neurips.cc/|NeurIPS Conference Videos]]
-[[https://www.exponentialview.co/newsletter/|Exponential View Newsletter]] has cool visualizations of data related to many current and future issues, such as environment and energy.
-[[https://www.theverge.com/2018/5/7/17316010/fast-ai-speed-test-stanford-dawnbench-google-intel|An AI speed test shows clever coders can still beat tech giants like Google and Intel]], by James Vincent, May 7, 2018
-[[https://lastweekin.ai/?triedSigningIn=true|Last Week in AI]]
-[[https://i2kconnect.com/ai-topics/| AAAI AI Alerts]], newsletter on recent AI news
-[[http://www.deeplearningweekly.com|Deep Learning Weekly]] newsletter: Check out [[https://nam01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdeeplearningweekly.us16.list-manage.com%2Ftrack%2Fclick%3Fu%3Dde53bead690affb8e9a21de8f%26id%3Dd826406963%26e%3Dd3d9a16e4c&data=02%7C01%7Cchuck.anderson%40colostate.edu%7C00f48b8f22284fee6d3808d76858d23b%7Cafb58802ff7a4bb1ab21367ff2ecfc8b%7C0%7C0%7C637092603010658440&sdata=c9K39Cd5Z94jfmRaX5wpweTcJncBiqliCz7QBywv8KE%3D&reserved=0|this Nov, 2019 video by Andrej Karpathy]], Head of AI at Tesla, summarizing Tesla's deep learning approach to self-driving cars.
-[[https://www.youtube.com/watch?v=aircAruvnKk|3Blue1Brown]] great youtube videos on neural networks.
-===== Python =====
-[[http://www.scipy-lectures.org/|Scipy Lecture Notes]]
-[[http://www.dataquest.io/blog/images/cheat-sheets/numpy-cheat-sheet.pdf|Numpy Cheat Sheet]]
-[[https://www.tutorialspoint.com/python_pandas/python_pandas_groupby.htm|Tutorial on using groupby and other functions in pandas.]]
-[[https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf|Pandas Cheat Sheet]],  very handy two pager.
-[[https://adventuresinmachinelearning.com/neural-networks-tutorial/|Neural Networks Tutorial]] (excellent introduction to neural nets with python and numpy)
-[[https://github.com/tirthajyoti/Machine-Learning-with-Python|Machine Learning with Numpy]] (very thorough set of jupyter notebooks as tutorials to numpy, pandas, neural networks, and other topics)
-[[https://mlfromscratch.com/neural-network-tutorial/#/|Neural Network Tutorial with Numpy]]
-[[https://realpython.com/blog/python/emacs-the-best-python-editor/|Emacs - the Best Python Editor?]]
-[[https://www.youtube.com/watch?v=5mDYijMfSzs|Installing and running python and jupyter notebook on Windows 10]]
-===== IDEs =====
-[[https://medium.com/dsights/visual-studio-code-for-data-science-the-more-i-use-more-i-like-ac668731dbb5|Visual Studio Code for Data Science]]
-[[https://medium.com/codex/how-to-debug-jupyter-notebooks-in-visual-studio-code-3d36039c6f86|How to Debug Jupyter Notebooks in Visual Studio Code]]
-[[https://www.jetbrains.com/pycharm/|Pycharm]]
-[[https://realpython.com/vim-and-python-a-match-made-in-heaven/|Vim]]
-[[https://realpython.com/emacs-the-best-python-editor/|Emacs]]
-===== Visualizations in Python =====
-[[https://pyviz.org/|PyVis]] A nice overview of visualization packages available in python.
-===== Math =====
-[[https://mml-book.github.io/|Mathematics for Machine Learning]], by  Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong.
-===== Notebook =====
-[[https://ljvmiranda921.github.io/notebook/2018/01/31/running-a-jupyter-notebook//|Running your jupyter notebook on a remote machine in general]];  [[https://sna.cs.colostate.edu/software/jupyter/|and specifically on our CS department's network of workstations]]
-[[https://github.com/Calysto/notebook-extensions|Spell checking and other extensions]]
-[[http://sourceforge.net/p/jupiter/wiki/markdown_syntax/|Markdown syntax]]
-[[https://github.com/jupyter/jupyter/wiki|A Gallery of Interesting Ipython Notebooks on Github]]
-[[https://www.kaggle.com/benhamner/d/uciml/iris/python-data-visualizations|Nice tutorial from Kaggle on using pandas and seaborn]]
-===== Reinforcement Learning =====
-[[http://www.kurzweilai.net/public-beta-of-toolkit-for-developing-machine-learning-for-robots-and-games-released?utm_source=KurzweilAI+Daily+Newsletter&utm_campaign=6b6f7717aa-UA-946742-1&utm_medium=email&utm_term=0_6de721fb33-6b6f7717aa-281946553|OpenAI Gym]]
-===== Data Sources =====
-[[https://blog.bigml.com/list-of-public-data-sources-fit-for-machine-learning/|Public Data Sources]]
-===== Writing Tips =====
-[[http://withoutbullshit.com/blog/10-top-writing-tips-psychology/|10 top writing tips and the psychology behind them]]
-===== Git and GitHub =====
-[[http://kbroman.org/github_tutorial/|git/github guide a minimal tutorial]]
-[[http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004668|A Quick Introduction to Version Control with Git and GitHub]]
-===== LaTeX =====
-[[http://www.latex-project.org|LaTeX]]
-[[https://www.overleaf.com/|Overleaf]] an on-line Latex service.
-[[https://www.authorea.com/|Authorea]] another on-line Latex (and other methods) service.