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Lukas Mendes's Projects

agenda icon agenda

Uma agenda para marcar clientes. Em puro Python.

air_pollution_data_science icon air_pollution_data_science

In this project I analyzed data on deaths from air pollution each year (From 1990 to 2017) in different countries. In the end I made several machine learning models to predict the number of deaths for the coming years. In this dataset, we have the number of deaths from various causes but I chose to focus only on those from air pollution. In the end I saved the best model.

black_jack icon black_jack

Um jogo de cartas, o Black Jack! Em puro Python. Foi um projeto de começo de carreira, vou melhora muito ele ainda.

customer_analysis_clustering icon customer_analysis_clustering

Project using machine learning to group customer profiles by their similarities, find patterns and guide assertive marketing strategies. In the end, based on the classes created by the K-means algorithm, we train models to classify new customers into one of the created classes.

deep_neural_network_pure_python_numppy icon deep_neural_network_pure_python_numppy

In this notebook, we are going to build a deep neural network with python and numpy. The file "dnn_utils.py" contains several functions that will be used here. Functions like forward prop and backprop, among many others. Please open this file to follow along. - Build and train a deep L-layer(the number of hidden layers the user assigns) neural network, and apply it to supervised learning.

time_series_petrobras_stock icon time_series_petrobras_stock

The objective of this project is to forecast stock prices for the company Petrobras, a state-owned Brazilian multinational corporation in the petroleum industry. We have the stock prices of 2013 to 2018. For this, we will use a Recurrent Neural Network (LSTM) and the Facebook Prophet algorithm. At the end we will compare the results between the models. Let's jump right in!

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