🏆The Kaggle Book — Master Data Analysis and Data Science Competitions with Machine Learning, GenAI, and LLMs [2nd Ed.]: http://amzn.to/4pxJpTC
Table of Contents:
🔶Introducing Data Science Competition
🔷Organizing Data with Datasets
🔶Work & Learn with Kaggle Notebooks
🔷Kaggle Models
🔶Leveraging Discussion Forums
🔷Detailing Competition Tasks & Metrics
🔶Designing Good Validation Schemes
🔷Modeling for Tabular Competitions
🔶Hyperparameter Optimization
🔷Ensembling & Stacking Solutions
🔶Modeling Image Classification & Segmentation
My Review (on Amazon):
This 700-page masterpiece of writing covers everything you need—start to finish—to be a competitive coder, specifically for Kaggle data science competitions. The book covers the mechanics of the competitions (platform, resources, rankings, leaderboards), then the infrastructure (notebooks, GitHub, data sets, frameworks, discussion forums), and then nearly 500 pages devoted to "Elevating Your Game" (in-depth coverage of modeling techniques, evaluation metrics, validation strategies, hyperparameter optimization, ensembles, stacking, and various categories of competitions: tabular data, computer vision, NLP, Gen AI, simulations). The book concludes with a valuable section on building your Kaggle portfolio for career advancement and new opportunities. This is an outstanding data science / AI / Machine Learning training resource for anyone, even if you are not into the competitions, though especially if you are a dedicated Kaggler.