The 12 days of Machine Learning-mas are beginner-friendly tutorials on the basics of machine learning. The tutorials will be streamed on Twitch, and the vods will be posted on YouTube. The code will be posted here following each lesson, and more detailed notes with deeper dives into the math and concepts will be posted following the event.
- Dec. 19th: Linear Regression
- Dec. 20th: Logistic Regression
- Dec. 21st: Classification
- Dec. 27th: Ensembling
- Dec. 28th: Unsupervised Machine Learning
- Dec. 29th: Anomaly Detection
- Dec. 30th: Intro to Reinforcement Learning
- Jan. 2nd: Neural Nets 101
- Jan. 4th: Reinforcement Learning Part II
- Jan. 6th: Network Analysis
- Jan. 7th: Natural Language Processing
- Jan. 8th: Computer Vision
Each tutorial will cover a specific topic or model in machine learning, and the code will be written in Python. Simpler models will be built in Jupyter Notebooks for ease of explanation and visualization, but later models will be script-only.
The code from each stream can be found in the notebooks folder and the blackboard notes in the blackboard folder. Detailed lecture notes, including math, relevant links, and whatnot will be added after the event has finished.
For more information or if you have questions, please join the Discord or reach out on Twitter.