Podcast Notes

07 May 2020 -

I’ve now listened to about forty episodes of various data science podcasts, including all episodes of Towards Data Science. I kept a running list of ideas, concepts, and people that I thought I would need to learn about while listening. I also had a bunch of blog ideas in this file but I have already shared them in the landing pages for each section of the blog. Here are the notes lists.

Books

• Data Science From Scratch - Done
• Building a Career in Data Science
• Atomic Habits - Reading
• Kaggle Reading Group
• Machine Learning Tokyo math reading group

Podcasts

• Adversarial Learning - Not that good
• Chai Time - First guest was good

People

• Mike Rowland - SQL
• Russel Pulari - Self Hacking

Programs

• Airflow
• Superset
• Presto
• Spark
• Streamlet
• HackerRank
• Narrative Science

Vocab

• Tensor - Kinda like a vector but with more info
• Docker - I think like a Jupyter Notebook
• PCA
• Why logistic regression?
• Causal Modeling
• Tech
• Justification of Learning

Practice

• Coding Models - Different modules for different preprocessing options
• Code Reviews
• Titanic Project

Review

• Linear Algebra