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data_modelling_plant_data_set.

Data modelling process for a real set with data from different types of plants.

deep_learning_research_project

Research Project in the area of ​​Deep Learning applied to credit risk. This model achieved better results compared to other published papers. This project is focused on the Fintech industry.

game_space_invaders

Group project with 3 other people. This game was developed using Python.

how_to_analytics_test

how_to_anomaly_detection

how_to_autoencoder

how_to_classification_problem

This is an example of how to use Python libraries for classification problems. Ideal for all those who want to learn simple ML techniques.

how_to_code_challenges

Learn how to solve the most common coding challenges

how_to_javascript

My own repository to learn JavaScript

how_to_neural_network

how_to_npl_rnn_cnn

In this repository we will check the concepts learned of NLP and RNN.

how_to_pandas_scikit-learn

how_to_python

how_to_regression_problem

This is an example of how to use Python libraries for regression problems. Ideal for all those who want to learn simple ML techniques.

how_to_sort_the_confusion_matrix

A common question when you're learning data science: "Sort the confusion matrix using your own function". This is a simple way to do it by using optimization.

how_to_unsupervised_learning

how_to_use_matlab_example

An example of how to use MATLAB to apply AI techniques in different projects. This example is ideal for anyone who has no MATLAB experience.

how_to_use_neo4j

This is a repository with information on how to use and learn Neo4j

how_to_web_development

The goal of this repo is to introduce the main aspects of front-end web development to create a website.

oordenesg

python-causality-handbook

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.

retail_real_data

Project with real retail data. This repository shows my proposed solution to estimate the sale using information obtained from IT sensors. Due to confidentiality issues, the entire data analysis and transformation process is not shown.