The following repository contains source code for a 100 Day personal machine learning coding challenge. It contains projects that I do as a part of my learning
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Updated
Feb 6, 2021 - Jupyter Notebook
The following repository contains source code for a 100 Day personal machine learning coding challenge. It contains projects that I do as a part of my learning
This pipeline provides a way to perform pharmaceutical compounds virtual screening using similarity-based analysis, ligand-based and structure-based techniques. The pipeline contains a collections of modules to perform a variety of analysis.
Modello Random Forest per la creazione di una mappa di suscettibilità da frane superficiali // // Tesi di Laurea Magistrale in Scienze della Terra (Geologia Applicata) - Università degli Studi di Milano
Machine Learning Software that predicts planets based on their distance from the sun, number of satellites and various properties
Análise de dados sobre cotas de gênero e seu impacto nas eleições e proposições legislativas da Câmara dos Deputados Federais entre 1934 e 2021. Parte do TCC da pós-graduação em Inteligência Artificial e Aprendizado de Máquina na @pucminas
My Python learning experience 📚🖥📳📴💻🖱✏
This project develops an activity recognition model for a mobile fitness app using statistical analysis and machine learning. By processing smartphone sensor data, it extracts features to train models that accurately recognize user activities.
Identification of fake currency is a challenging problem for all. Fake banknotes are becoming more and more identical to the real ones. In this Fake Currency Detection model, I have used multiple machine learning algorithms to determine fake or real banknotes and was able to achieve more than 90% accuracy.
A parser for scikit-learn exported text models to execute in the Java runtime.
Machine learning model Visualizer in web using streamlit
Repository for the ENSF 612 final project.
Final Project Of Computational Intelligence - Fall 2021 - LightGBM, RandomForest and StackingClassifier
Build a Machine Learning model that is able to classify whether or not a person believes in climate change, based on their novel tweet data
Natural Language Processing
ML models for HR classification problem. For more information please visit the link: https://datahack.analyticsvidhya.com/contest/wns-analytics-hackathon-2018-1/
In this project I intend to predict customer churn on bank data.
The Aim of this project is used to identify whether a new transaction is fraudulent or not.
Disaster Tweets Classifications by Machine Learning, which is a currently Kaggle Competition.
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