Term Deposit Subscription Prediction Model
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Updated
Jul 13, 2023 - HTML
Term Deposit Subscription Prediction Model
A dengue prediction model created as a part of Environment Studies offered in S4, CSE NITC
In the project we built the following algorithms : Decision Tree Classifiier and Regressor, AdaBoost Classifiier , Gradient Boost Regressor
This repository contains code for my Machine Learning Basic Nanodegree Project.
Help Carvana determine which cars should be avoided at used car auctions
Lead prediction case. Used GBM, RandomForest Linear Regression on H2O package
Kaggle's: Machine Learning from Otto Group Product Classification Challenge. Demonstrates basic machine learning, analysis, and visualization techniques.
Predicting Wine Quality with Random Forest Algorithm
Pump it Up, Data Mining the Tanzania Water Table
This projects contains a work of data mining with various machine learning and deep learning techniques
6th Project for the Post Graduate Programme in Data Science and Business Analytics at the University of Texas at Austin - Model Tuning (GridSearchCV & RandomizedSearchCV)
This project explores the working of various Boosting algorithms and analyzes the results across different algorithms. Algorithms Used are: Random Forest, Ada Boost, Gradient Boost and XG Boost
Learning whilst drilling through real-time, near-bit prediction ahead of the drill-bit, using offset well log data.
Price diamonds using regression and decision tree models
A churn prediction case study focused on cleaning, analyzing, and modeling ride-sharing data aimed at seeking the best predictors for retention
This repository has been created for Udacity Data Scientist Nanodegree Program - Supervised Learning Part - Finding Donors for CharityML Project
Finding Donor for CharityML - Machine Learning Nanodegree from Udacity
Supervised Learning - Finding Potential Donors for CharityML
This repository is dedicated to the study of functional trait divergence using machine learning methodologies. It encompasses datasets, code, tables, and visual representations pertinent to the research.
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