Pietro Monticone's repositories
pitmonticone
Profile repository of Pietro Monticone.
amazon-sagemaker-examples
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
NonlinearDynamicsComplexSystemsCourse
Material for a full course on applied nonlinear dynamics, nonlinear timeseries analysis, and complex systems, in Julia
waterproof
Waterproof is an educational environment for writing mathematical proofs in interactive notebooks. See the readme file for install instructions.
Bayesian-Julia
Bayesian Statistics using Julia and Turing
Bayesian-Statistics
This repository holds slides and code for a full Bayesian statistics graduate course.
book
The "Assumptions of Physics" book
communitynotes
Documentation and source code powering Twitter's Community Notes
cornell-cs5785-2023-applied-ml
Lecture materials for Cornell CS5785 Applied Machine Learning (Fall 2023)
deeplearning-models
A collection of various deep learning architectures, models, and tips
formalisation
Website for the formalisation of mathematics and Lean event in Rome
gaagc24.github.io
Website for Group Actions: algebraic, geometric and combinatorial aspects
gemma
Open weights LLM from Google DeepMind.
homotopy-type-theory-course
A course on homotopy theory and type theory, taught jointly with Jaka Smrekar
intro_dgm
"Deep Generative Modeling": Introductory Examples
LeanCopilot
Native Neural Network Inference in Lean
maths-notes
Lecture notes from Cambridge maths
ml-engineering
Machine Learning Engineering Guides and Tools
PairPlots.jl
Beautiful and flexible vizualizations of high dimensional data
penzai
A JAX research toolkit for building, editing, and visualizing neural networks.
PNT
blueprint for prime number theorem and more
proofs-and-programs-2023
Code and source for website for the course "Proofs and Programs", January 2023, Indian Institute of Science
STG4
Set Theory Game
turinglang.github.io
The home for all Turing website & documentation resources.
uvadlc_notebooks
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2021/Spring 2022