alessandromiola Goto Github PK

adventofcode

My attempt to solve advent-of-code puzzles

alessandromiola

annotated_deep_learning_paper_implementations

🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

auth-in-fastapi-notes

Assorted notes on authentication and authorization in FastAPI

bear

Python Biella Group basic template for a modern generic python application

bertviz

BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)

bitcoin

Bitcoin Core integration/staging tree

bitcoinblockchaintechnology

Material for the Bitcoin & Blockchain Technology course

category_encoders

A library of sklearn compatible categorical variable encoders

cleanlab

The standard package for machine learning with noisy labels and finding mislabeled data. Works with most datasets and models.

confidentialtransactionsdoc

A detailed description of how Bitcoin Elements Alpha Confidential Transactions works

course

The Hugging Face course on Transformers

course-nlp

A Code-First Introduction to NLP course

covidfit

Fit data from pcm-dpc / COVID-19

data-engineering-zoomcamp

Free Data Engineering course!

dginst.github.io

Repo for the Digital Gold Institutel website

fastapi-blog-course

flights-scraper-web-app

grin

Minimal implementation of the MimbleWimble protocol.

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

hypopt

⏸ Parallelized hyper-param optimization with validation set, not crossval

inseq

Interpretability for sequence generation models 🐛 🔍

learning-bitcoin-from-the-command-line

The best way to learn to learn deeply about bitcoin is to avoid GUIs (even bitcoin-qt), and instead learn it from the command line.

mlbookcamp-code

The code from the Machine Learning Bookcamp book and a free course based on the book

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 ;)

programmingbitcoin

Repository for the book

pydantic

Data validation using Python type hints

pydantic-notes

Personal repo to explore and test pydantic functionalities

pytorch-deep-learning

Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.