CS545: Machine Learning

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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]]

Negative posts regarding high-tech jobs:

[[https://d-hanshew.medium.com/the-hidden-cost-of-high-salaries-in-tech-4e5d8c9b2e3a|The Hidden Cost of High Salaries in Tech]]

[[https://levelup.gitconnected.com/why-developers-leave-google-5c4037b39e0a|Why Developers Leave Google]]

[[https://medium.com/stories-from-heart/google-is-not-just-firing-employees-its-doing-something-even-worse-df38217b0452|Google is not just firing employees, it is doing something even worse!]]

===== 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.

===== Hot Topics =====

[[https://arxiv.org/abs/2308.08708|Consciousness in Artificial Intelligence: Insights from the Science of Consciousness]]


===== 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://www.youtube.com/watch?v=h1sAzPojKMg|Get started with Jupyter Notebooks in less than 4 minutes]]

[[https://www.youtube.com/watch?v=B-s71n0dHUk|Learn Visual Studio Code in 7min (Official Beginner Tutorial|https://www.youtube.com/watch?v=B-s71n0dHUk]]

[[https://www.youtube.com/watch?v=DA6ZAHBPF1U|Jupyter Notebooks in VS Code Walkthrough]]

[[https://www.youtube.com/watch?v=QJo57-pmcuM|5 things you had no idea you could do with Jupyter Notebooks (in VS Code)]]

[[https://www.youtube.com/watch?v=5pf0_bpNbkw|Jupyter Notebook Complete Beginner Guide 2023 - From Jupyter to Jupyterlab, Google Colab and Kaggle]], and other videos by Rob Mulla

[[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]]

[[https://www.youtube.com/watch?v=JYKkUF7IBRo|Emacs vs VS Code]]

===== Jupyter Notebook =====

[[https://towardsdatascience.com/debugging-jupyter-notebooks-will-boost-your-productivity-a33387f4fa62|Debugging Jupyter Notebooks Will Boost Your Productivity]]



[[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]]

===== 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.


===== Use of GPU =====

[[https://www.youtube.com/watch?v=auksaSl8jlM|JAX installation with Nvidia CUDA and cudNN support]] help with fixing most common installation errors. Might help with pytorch and tensorflow also.

===== Reinforcement Learning =====

[[http://incompleteideas.net/book/the-book-2nd.html|Reinforcement Learning: An Introduction, by R. Sutton and A. Barto]]

[[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.