Jorge Bezerra's starred repositories
municipios-brasileiros
:house_with_garden: Dados relacionados aos municípios brasileiros
ml-design-patterns
Source code accompanying O'Reilly book: Machine Learning Design Patterns
handson-ml
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
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.
grokking_algorithms
Code for the book Grokking Algorithms (https://amzn.to/29rVyHf)
retentioneering-tools
Retentioneering: product analytics, data-driven CJM optimization, marketing analytics, web analytics, transaction analytics, graph visualization, process mining, and behavioral segmentation in Python. Predictive analytics over clickstream, AB tests, machine learning, and Markov Chain simulations.
cookiecutter-data-science
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
pmlab-full
Process Mining scripting environment
pm4py-core
Public repository for the PM4Py (Process Mining for Python) project.
ML-For-Beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
GeneticAlgorithmProductionPlanning
Example of Solving a Production Planning Problem with Genetic Algorithm
python-coding-interview
A middle-to-high level open source algorithm book designed with coding interview at heart!
Decision-Tree-Regression
Decision Tree is a decision-making tool that uses a flowchart-like tree structure or is a model of decisions and all of their possible results, including outcomes, input costs and utility. Decision-tree algorithm falls under the category of supervised learning algorithms. It works for both continuous as well as categorical output variables.Decision tree regression observes features of an object and trains a model in the structure of a tree to predict data in the future to produce meaningful continuous output. Continuous output means that the output/result is not discrete, i.e., it is not represented just by a discrete, known set of numbers or values.
Markov-Decision-Process-Toolbox-Practice_Simple
A Markov decision process (MDP) is a discrete time stochastic control process. It provides a mathematical framework for modeling decision making in situations where outcomes are partly random and partly under the control of a decision maker.
Project-1-Reinforcement-Learning
Reinforcement Learning in a discrete Domain project, in the context of the "Optimal decision making for complex problems" class
Reinforcement_learning_based_PID_Tuner
The implemetation of the Reinforcement Learning based PID Tunner.
coding-interview-university
A complete computer science study plan to become a software engineer.