Daniel Cestari's starred repositories
machine_learning_basics
Plain python implementations of basic machine learning algorithms
statsforecast
Lightning ⚡️ fast forecasting with statistical and econometric models.
data-science-at-the-command-line
Data Science at the Command Line
ML_Finance_Codes
Machine Learning in Finance: From Theory to Practice Book
whatsapp-purple
WhatsApp protocol implementation for libpurple (pidgin)
mlforecast
Scalable machine 🤖 learning for time series forecasting.
purple-gowhatsapp
Pidgin/libpurple plugin for WhatsApp Web.
tdlib-purple
libpurple Telegram plugin using tdlib
ARC-solution
Code for 1st place solution to Kaggle's Abstraction and Reasoning Challenge
Regression-Loss-Functions-in-Time-Series-Forecasting-Tensorflow
This repository contains the implementation of paper Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting with different loss functions in Tensorflow. We have compared 14 regression loss functions performance on 4 different datasets.
TopoBenchmarkX
TopoBenchmarkX is a Python library designed to standardize benchmarking and accelerate research in Topological Deep Learning
pidgin-pushbullet
A Pushbullet plugin for Pidgin
KAN-Continual_Learning_tests
Collection of tests performed during the study of the new Kolmogorov-Arnold Neural Networks (KAN)
ETL_pipeline_tick_data_B3
Este código busca exemplificar um pipeline ETL (Extract, Transform, Load) usando Python. Mantive o formato .ipynb (notebook) para facilitar o acompanhamento da rotina por iniciantes. Ele está dividido em três etapas: 1) Extração de múltiplos dados via webscraping; 2) Transformação dos dados; 3) Carregar os dados já estrurados para um database;
Knowledge-Graph
how to build up Knowledge graph
libpurple-feed
A RSS and Atom feed reader plugin for libpurple based messengers like Pidgin, Finch, Adium and others
tdlib-purple
libpurple Telegram plugin using tdlib