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This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD).
This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD) with MRI data.
Uses letter frequency and catboost classifier model in synchronous for guessing letters in hangman game instance. The model performance is evaluated on both seen words in the dictionary and words out of the dictionary.
Командный проект по Векторной электрокардиографии
Classifying if a landslide occured or not
Android malware detection using machine learning.
A model on the streamlit framework predicts disease and makes a treatment recommendation
This is my final solution to the Mars-spectrometry challenge by NASA hosted on @drivendataorg
A Domestic violence support system for the victims, that enables users to share their thought and provides knowledge about the particular type of abuse they are going through.
Multimodal Sentiment Analysis using Text and Image Data on twitter dataset
Web Server Log Analysis
Machine Learning aplicado al mantenimiento predictivo. Se realizaron 2 modelos: 1 por medio de clasificación binaria que predice si una máquina fresadora estará en riesgo de fallar o no, y el 2 modelo a través de clasificación multiclase que predecirá el modo de falla
A model classifying whether a person would survive on Titanic
This repo includes Cardiac arrest prediction part, path planning, and landing system of the quadcopter.
auto avia offer in Aeroclub hackathon
Discover a comprehensive approach to constructing credit risk models. We employ various machine learning algorithms like LightGBM and CatBoost, alongside ensemble techniques for robust predictions. Our pipeline emphasizes data integrity, feature relevance, and model stability, crucial elements in credit risk assessment.
Data Analysis and prediction on Kaggle dataset: Credit Risk Dataset
Expresso Churn Prediction Challenge - dealing with imbalanced dataset
Identify health insurance customers with interest in a vehicle insurance.
New User Engagement
Disaster Tweets Classifications by Machine Learning, which is a currently Kaggle Competition.
bank marketing prediction for a term deposit campaign, identify non-potential customers
This project predicts MBTI personality types from users' recent 50 posts using NLP and ML techniques.
The Credit Card Fraud Detection Problem includes modeling past credit card transactions with the knowledge of the ones that turned out to be a fraud. This model is then used to identify whether a new transaction is fraudulent or not. Our aim here is to detect 100% of the fraudulent transactions while minimizing the incorrect fraud classifications.
We all have experienced a time when we have to look up for a new house to buy. But then the journey begins with a lot of frauds, negotiating deals, researching the local areas and so on. So to deal with this kind of issues Today, I prepared a MACHINE LEARNING Based model, trained on the House Price Prediction Dataset.
ML competition submission to classify anonymous age related condition
Machine learning to predict which passengers survived the Titanic shipwreck
Evaluating Hyperopt, Optuna, and TunedThresholdClassifierCV
The purpose is to train a predictive model that can determine if a given customer will subscribe to a term deposit based on these various features. By analyzing historical data on successful and unsuccessful subscription outcomes, patterns can be identified which help predict future subscription behavior.
Kaggle competition on network intrusion detection. Train model, predict test set, submit as CSV (ID, Class). F1-score metric. Part of my 2023 master's program at the University of Ottawa in AI for Cyber Security.
This project develops an advanced predictive model to identify thyroid disease recurrence using machine learning algorithms. We used a detailed dataset with demographic, medical, and clinical features, and implemented Logistic Regression, Decision Tree, Random Forest, and CatBoost Classifier. Rigorous preprocessing and EDA were performed.
Credit_Card_Approval_odinschool_project