-
PhD in Machine Learning
- Brazil
- https://smastelini.github.io/
- https://orcid.org/0000-0002-0092-3572
- in/smastelini
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Starred repositories
Versatile audio super resolution (any -> 48kHz) with AudioSR.
Intelligent automation and multi-agent orchestration for Claude Code
🚀🤖 Crawl4AI: Open-source LLM Friendly Web Crawler & Scraper. Don't be shy, join here: https://discord.gg/jP8KfhDhyN
AirLLM 70B inference with single 4GB GPU
🚲 Git scraping for bike sharing APIs
An open access book on scientific visualization using python and matplotlib
This repo includes ChatGPT prompt curation to use ChatGPT and other LLM tools better.
Mkdocs plugin to add plots from data using vegalite
⚡ Dynamically generated stats for your github readmes
🚕 Self-contained demo using Redpanda, Materialize, River, Redis, and Streamlit to predict taxi trip durations
How to do Bayesian statistical modelling using numpy and PyMC3
min(DALL·E) is a fast, minimal port of DALL·E Mini to PyTorch
🙃 A delightful community-driven (with 2,400+ contributors) framework for managing your zsh configuration. Includes 300+ optional plugins (rails, git, macOS, hub, docker, homebrew, node, php, python…
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
Vim-fork focused on extensibility and usability
👑 Multivariate exploratory data analysis in Python — PCA, CA, MCA, MFA, FAMD, GPA
Generation of diagrams like flowcharts or sequence diagrams from text in a similar manner as markdown
Django plugin for online machine learning with river (under-development)
🔤 Measure edit distance based on keyboard layout
t-Digest data structure in Python. Useful for percentiles and quantiles, including distributed enviroments like PySpark
☀️ Measuring the accuracy of BBC weather forecasts in Honolulu, USA
The simplest way to deploy a machine learning model
A unified framework for machine learning with time series
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
A curated list of gradient boosting research papers with implementations.