Edoardo Abati's starred repositories
scikit-learn
scikit-learn: machine learning in Python
Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
sentence-transformers
Multilingual Sentence & Image Embeddings with BERT
data-science-interviews
Data science interview questions and answers
approachingalmost
Approaching (Almost) Any Machine Learning Problem
NYU-DLSP20
NYU Deep Learning Spring 2020
nlp-recipes
Natural Language Processing Best Practices & Examples
python-machine-learning-book-3rd-edition
The "Python Machine Learning (3rd edition)" book code repository
ml-interviews-book
https://huyenchip.com/ml-interviews-book/
mlops-course
Learn how to design, develop, deploy and iterate on production-grade ML applications.
MLE-Flashcards
200+ detailed flashcards useful for reviewing topics in machine learning, computer vision, and computer science.
ml-design-patterns
Source code accompanying O'Reilly book: Machine Learning Design Patterns
nlp_paper_summaries
✍️ A carefully curated list of NLP paper summaries
practical-nlp-code
Official Repository for Code associated with 'Practical Natural Language Processing' book by O'Reilly Media
Deep-Learning-In-Production
Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.
ctci-python-solutions
Cracking the Coding Interview in Python 3. The solutions all have detailed explanations with visuals.
pyspark-style-guide
This is a guide to PySpark code style presenting common situations and the associated best practices based on the most frequent recurring topics across the PySpark repos we've encountered.
high_performance_python_2e
Code for the book "High Performance Python 2e" by Micha Gorelick and Ian Ozsvald with OReilly
practical-docker
Demo code for my O'Reilly "Practical Docker" presentation