MarcoGrippa

MarcoGrippa's Stars

• Developer-Y/cs-video-courses

  List of Computer Science courses with video lectures.

  67.5k1.9k1439.2k

• jakevdp/PythonDataScienceHandbook

  Python Data Science Handbook: full text in Jupyter Notebooks

  Language:Jupyter Notebook43.4k1.8k19418k

• ml-tooling/best-of-ml-python

  🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

  18.3k418562.5k

• PrefectHQ/prefect

  Prefect is a workflow orchestration framework for building resilient data pipelines in Python.

  Language:Python17.8k1655.8k1.7k

• microsoft/nni

  An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

  Language:Python14.1k2842.1k1.8k

• axa-group/Parsr

  Transforms PDF, Documents and Images into Enriched Structured Data

  Language:JavaScript5.9k82163310

• online-ml/river

  🌊 Online machine learning in Python

  Language:Python5.1k85607552

• clauswilke/dataviz

  A book covering the fundamentals of data visualization

  Language:HTML3.2k113100700

• ml874/Data-Science-Cheatsheet

  Language:TeX2.5k1308613

• NannyML/nannyml

  nannyml: post-deployment data science in python

  Language:Python2k21104145

• JulienPalard/Pipe

  A Python library to use infix notation in Python

  Language:Python2k2550114

• ABZ-Aaron/CheatSheets

  Just a place to store cheatsheets

  1.7k741274

• DeepWisdom/AutoDL

  Automated Deep Learning without ANY human intervention. 1'st Solution for AutoDL challenge@NeurIPS.

  Language:Python1.1k3240215

• MaurizioFD/RecSys2019_DeepLearning_Evaluation

  This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.

  Language:Python9853914249

• vizzuhq/ipyvizzu-story

  Build, present and share animated data stories in Jupyter Notebook and similar environments.

  Language:Jupyter Notebook32682230

• AstraZeneca/awesome-shapley-value

  Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)

  1442012

• ChungYi347/Interactive-Multi-Class-Tiny-Object-Detection

  Language:Python14131211

• PlantsAndPython/PlantsAndPython

  Language:Jupyter Notebook267713

• masedos/Bootcamp-Cientista-de-Dados

  Bootcamp Cientista de Dados realizado pela IGTI

  Language:Jupyter Notebook17505

• d2cml-ai/14.388_py

  This material has been created based on the tutorials of the course 14.388 Inference on Causal and Structural Parameters Using ML and AI in the Department of Economics at MIT taught by Professor Victor Chernozukhov. All the scripts were in R and we decided to translate them into Python, so students can manage both programing languages. Jannis Kueck and V. Chernozukhov have also published the original R Codes in Kaggle. In adition, we included tutorials on Heterogenous Treatment Effects Using Causal Trees and Causal Forest from Susan Athey’s Machine Learning and Causal Inference course. We aim to add more empirical examples were the ML and CI tools can be applied using both programming languages.

  Language:Jupyter Notebook16121

• Wiryco/Bootcamp-IGTI-Analista-de-Dados

  Bootcamp online analista de dados disponibilizado pelo IGTI – Instituto de Gestão e Tecnologia da Informação

  Language:Jupyter Notebook14204

• d2cml-ai/14.388_r

  This Jupyterbook has been created based on the tutorials of the course 14.388 Inference on Causal and Structural Parameters Using ML and AI in the Department of Economics at MIT taught by Professor Victor Chernozukhov.

  Language:Jupyter Notebook12012

• d2cml-ai/mgtecon634_py

  This tutorial will introduce key concepts in machine learning-based causal inference. This tutorial is used by professor Susan Athey in the MGTECON 634 at Stanford. Scripts were translated into Python.

  Language:Jupyter Notebook12006

• d2cml-ai/mgtecon634_r

  This tutorial will introduce key concepts in machine learning-based causal inference. This tutorial is used by professor Susan Athey in the MGTECON 634 at Stanford.

  Language:Jupyter Notebook8024

• mateusbtlopes/fazendo-bi-do-zero

  Passo a passo de como fazer um projeto de BI (Business Intelligence) do planejamento aos testes de dashboards.

  Language:TSQL8202

• Collumbus/Bootcamp-Analista-de-Dados-IGTI

  Language:Jupyter Notebook5201

• LawrenceDuan/IMDb-Review-Analysis

  Using sentiment analysis to classify documents based on their polarity. In particular, this project works with a dataset of 50,000 movie reviews from the Internet Movie Database (IMDb) and build a predictor that can distinguish between positive and negative review.

  Language:Python5401

• jomarsilio/Bootcamp-IGTI-Analista-de-Dados

  Bootcamp ministrado pela IGTI com o objetivo de abordar de forma intensiva conceitos e práticas da análise de dados, habilitando o aluno para atuar profissionalmente na área.

  Language:Jupyter Notebook4200

• saurater/ciencias_de_dados_estatistica

  IGTI - Ciências de Dados - Lab

  Language:Jupyter Notebook23

• leosimoes/IGTI-Bootcamps-Dados

  Atividades práticas realizadas durante os bootcamps Cientista de dados e Analista de Machine Learning do IGTI.

  Language:Jupyter Notebook1100