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ab_test_guide_in_python

from https://towardsdatascience.com/ab-testing-with-python-e5964dd66143

academy

Ray tutorials from Anyscale

amazon_ds_challenge

Data challenge job interview for an AWS Research Scientist position - Sydney (Nov, 2017)

an_introduction_to_statistical_learning

bayesian_statistics_the_fun_way

This repository have all the exercises of the book:

bigdata_docker

Big Data Ecosystem Docker

causal_inference_python_code

Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins

clean-code-in-python

Clean Code in Python, published by Packt

coding_problems

Hacker Hank, Codilify and coding problems, all to don't give up of my problem solving skills using regular data structures (no dataframes and pandas functions are allowed).

data_science_references

This is a space to keep and share good references for study material for Data Science, Programming and Statistics.

data_structures_in_c

Old projects in C language

dataviz

A book covering the fundamentals of data visualization

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

ever2simple

Migrate from evernote to simplenote with markdown formatting

explainable_ai

Using LIME and SHAP models to explain some models in sklearn

fundamentals_of_reinforcement_learning

Fundamentals of Reinforcement Learning University of Alberta, Alberta Machine Intelligence Institute

gaming_industry_domain_knowledge

This is a repository to keep, study and share links, books and all related to Data Analytics on gaming Industry.

generative-ai-for-beginners

12 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

google-python-exercises.

Coding exercises https://developers.google.com/edu/python?hl=en&authuser=1

gym

A toolkit for developing and comparing reinforcement learning algorithms.

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.

hyperopt_mlflow

Parameter Tuning with Hyperopt using Bayesian Optimisation and MLFlow

ifood-data-business-analyst-test

iFood Brain team data challenge for Data Analysts role

kaggle_competitions

This is a Kaggle competitions repository with python notebooks where I'm playing around using data analysis and machine learning tools.

lastfmdataset

This Dataset is a mix of LastFM Artists listened and a map with DBPedia Ontology (metadata). For each Artist there are a link to DBPedia ontology.

lodrecsys15

RecSys 2015 challenge, using Linked Open Data to improve the diversity of Recommender Systems

mais-saude

Mineração de dados de gastos e desempenho e saúde dos municípios da PB (WIP)

maisedu

Que municípios gastam bem em educação? Mineração de gastos e desempenho na PB.

metagame

Compute metagame bounds from matchup charts.

ml-foundations

Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science