Nailson Boaz's repositories
amazon_ds_challenge
Data challenge job interview for an AWS Research Scientist position - Sydney (Nov, 2017)
ab_test_guide_in_python
from https://towardsdatascience.com/ab-testing-with-python-e5964dd66143
academy
Ray tutorials from Anyscale
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
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"
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
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
ml_algorithms_python
Machine Learning from scratch in Python (this says everything that you need to know) - The year is 2020, a global pandemic is taking over our lives, the quarantine gave me the time and strength needed to start this bold project.
mml-book.github.io
Companion webpage to the book "Mathematics For Machine Learning"
Optimization-Python
General optimization (LP, MIP, QP, continuous and discrete optimization etc.) using Python
python-causality-handbook
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
reinforcement_learning
Exercises of Hands-On Machine Learning Chapter 18 - Reinforcement Learning
scala-functional-programming
Functional Programming Principles in Scala - Coursera Course