15 DS/ML Cheat Sheets

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This post collates 15 cheat sheets covering essential data science and machine learning concepts. It includes resources on translating between different data manipulation libraries, multi-GPU training strategies, testing ML models in production, neural network optimization, and more. Detailed links are provided for further reading.

#machine-learning

#data-science

#neural-networks

#numpy

Sep 22, 2024•4m read time•From blog.dailydoseofds.com

Table of contents

#1) 15 Pandas ↔ Polars ↔ SQL ↔ PySpark Translations #2) 4 Strategies for Multi-GPU Training #3) 4 Ways to Test ML Models in Production #4) 15 Ways to Optimize Neural Network Training #5) Training and Inference Time Complexity of 10 ML Algorithms #6) 5 LLM Fine-tuning Techniques Explained Visually #7) NumPy Cheat Sheet Of 40 Most Used Methods #8) Most Important Plots in Data Science #9) Must-know Data Science Glossary #10) 10 Regression and Classification Loss Functions #11) 11 Types of Variables in a Dataset #12) 7 Categorical Data Encoding Techniques #13) 20 Most Common Magic Methods #14) Full-model Fine-tuning vs. LoRA vs. RAG #15) Transfer Learning, Fine-tuning, Multitask Learning and Federated Learning For those who want to build a career in DS/ML on core expertise, not trends:SPONSOR US