Contains our Approach for the competition organized at Udyam'21
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Updated
Apr 20, 2021 - Jupyter Notebook
Contains our Approach for the competition organized at Udyam'21
A machine learning pipeline for classifying cybersecurity incidents as True Positive(TP), Benign Positive(BP), or False Positive(FP) using the Microsoft GUIDE dataset. Features advanced preprocessing, XGBoost optimization, SMOTE, SHAP analysis, and deployment-ready models. Tools: Python, scikit-learn, XGBoost, LightGBM, SHAP and imbalanced-learn
A machine learning based forecasting system for taxi demand prediction
This project is about to detecting the text generated by different LLM given prompt. The instance is labeled by Human and Machine, and this project utilised both traditional machine learning method and deep learning method to classify the instance.
Implémentation d'un modèle de scoring (OpenClassrooms | Data Scientist | Projet 7)
This approach has the potential to create accurate, generalizable and adaptable machine learning methods that effectively and sustainably address agricultural tasks such as yield prediction and early disease identification.
Predicting transaction fraud using classification problems such as Guardian Boosting as well as user interfaces using Streamlite
It's the Repo having a .ipynb file with bank customer churn prediction using various classifiers and machine learning models
Music Genre Recommender website that can identify and recommend 10 different genres of music using Light Gradient Boosting Machine (LGBM). An accuracy of 90% was achieved on the test set by tuning the hyperparameters of the model with Optuna.
End to end Heart Diseases Prediction Model with webapp using Flask
This repository contain my final projekt on the Data science Skillbox school on the topic: "Development of a machine learning algorithm to predict the behavior of customers of the "SberAvtopodpiska"
Various classification algorithms are implemented to predict whether a person is prone to or is suffering from heart disease.
Participated in Analytics Vidya Hackathon ( JOB-A-THON | May 2021 ). This Repository contains all code, reports and approach.
Identifying Giants and Dwarfs Stars through Machine Learning
Predicting Next Booking Destinations for Airbnb Users. Feel free to access the Streamlit App in the link below.
Bank Churn Classification
This project tackles the growing concern of obesity by developing a model to predict an individual's risk. By analyzing various factors, we aim to identify people who might be more susceptible to weight gain and related health problems.
Loan Eligibility - Classification (Python)
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