Table of Contents
Useful Links
This page will contain links to helpful on-line material.
Jobs in Machine Learning
ML jobs, a few near Fort Collins
Negative posts regarding high-tech jobs:
The Hidden Cost of High Salaries in Tech
Google is not just firing employees, it is doing something even worse!
Recent News
Distill, useful explanations of machine learning concepts.
Towards Data Science, introductions and tutorials related to machine learning
Exponential View Newsletter has cool visualizations of data related to many current and future issues, such as environment and energy.
An AI speed test shows clever coders can still beat tech giants like Google and Intel, by James Vincent, May 7, 2018
AAAI AI Alerts, newsletter on recent AI news
Deep Learning Weekly newsletter: Check out this Nov, 2019 video by Andrej Karpathy, Head of AI at Tesla, summarizing Tesla's deep learning approach to self-driving cars.
3Blue1Brown great youtube videos on neural networks.
Hot Topics
Python
Tutorial on using groupby and other functions in pandas.
Pandas Cheat Sheet, very handy two pager.
Neural Networks Tutorial (excellent introduction to neural nets with python and numpy)
Machine Learning with Numpy (very thorough set of jupyter notebooks as tutorials to numpy, pandas, neural networks, and other topics)
Neural Network Tutorial with Numpy
Emacs - the Best Python Editor?
Installing and running python and jupyter notebook on Windows 10
IDEs
Get started with Jupyter Notebooks in less than 4 minutes
Jupyter Notebooks in VS Code Walkthrough
5 things you had no idea you could do with Jupyter Notebooks (in VS Code)
Jupyter Notebook Complete Beginner Guide 2023 - From Jupyter to Jupyterlab, Google Colab and Kaggle, and other videos by Rob Mulla
Visual Studio Code for Data Science
Jupyter Notebook
Debugging Jupyter Notebooks Will Boost Your Productivity
Running your jupyter notebook on a remote machine in general; and specifically on our CS department's network of workstations
Spell checking and other extensions
Visualizations in Python
PyVis A nice overview of visualization packages available in python.
Math
Mathematics for Machine Learning, by Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong.
Use of GPU
JAX installation with Nvidia CUDA and cudNN support help with fixing most common installation errors. Might help with pytorch and tensorflow also.