This is my college practice work, where i try to learn and cover all the tree based regression algorithms (preferably in python).
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Updated
Dec 2, 2020 - Jupyter Notebook
This is my college practice work, where i try to learn and cover all the tree based regression algorithms (preferably in python).
This is my college practice work, where i try to learn and cover all the regression algorithms (preferably in python)
🏡 Empower property market decisions with a machine learning model predicting house prices using the Boston Housing dataset. 💸🏠💹
Predict Global Competitiveness merupakan program memprediksi value dari Global Competitiveness Index yang setelah tahun 2019 tidak kunjung dikeluarkan oleh pihak bank dunia, program ini merupakan salah satu alternative untuk melihat score GCI dengan menggunakan data Socio-Economics dan Enviromental Indicator
Machine Learning Projects
In this repository, delve into the realm of regression modeling featuring an array of algorithms applied to diverse datasets. Explore the strengths and nuances of different regression techniques, providing a comprehensive overview for anyone interested in predictive modeling.
The latex code of my bachelor thesis at Sapienza University of Rome
Machine Learning Regression use case notebooks
🚗 Engineered a high-performing car price prediction model, empowering informed decisions in the dynamic car market. 🚘💰
CODSOFT Data Science Internship Project Tasks.
Data analysis with Python to building and evaluating data models.
Agricultural Yield and Population Forecasting: Utilizing machine learning to enhance crop yield and predict global population trends, informing sustainable development and policy decisions.
🚗 Engineered a high-performing car price prediction model, empowering informed decisions by Identifying the key features that most influence car prices in the market. 🚘💰
This repo covers the basic machine learning regression projects/problems using various machine learning regression techniques and MLP Neural Network regressor through scikit learn library
Protein-protein interaction Binding Affinity Prediction
Multi-Linear and Binary Logistic Regression in C.
This project aims to build a predictive model that could predict the number of rental bikes required for each hour using the Seoul Bike Sharing dataset. Linear regression, Lasso (L1), Ridge (L2), ElasticNet, Decision Tree, Random Forest, and XGBoost algorithms are used to build a model to predict the number of rental bikes required for each hour.
The objective of this project is to study the COVID-19 outbreak using basic statistical techniques and make short term predictions using ML regression methods.
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