My 2022 Year in Review as a Data Scientist
Reading, writing, studying, speaking, and community service
2022 has gone by so fast. What did I do this year? Here is my 2022 year in review as a data scientist.
In 2022, I started many data science books but only finished five data science books cover to cover:
What is my favorite? I like all these books. If I have to pick a favorite, it is Designing Machine Learning Systems by Chip Huyen. I really like Chip’s writing style. She explains all the important ML concepts and MLOps practices in a clear and engaging way. Chip inspires me to be a better writer and ML practitioner. I made a video summarizing this book, check it out if you are interested:
The rest of the four books are top picks from my book club. Yes, I have started a DS/ML book club this year. I don’t like the traditional book clubs and I like to have a place to discuss books with people asynchronously, so I started a book club on Discord (linked at the end of the article). Our book club votes on the books we’d like to read each month and we were very fortunate to chat with the book authors in the book club. All of the book authors are incredibly generous and knowledgeable:
- Joe Reis and Matt Housley’s Fundamentals of Data Engineering centers around the data engineering lifecycle and explains everything you need to know about data engineering. I like that this book does not focus on a single tech stack, but rather explains the core concepts and principles of data engineering. I think this book is a must-read for all data professionals.