This project implements various machine learning algorithms from scratch using Python and NumPy, without relying on external libraries such as TensorFlow, Keras, or scikit-learn. The implemented algorithms include classification, regression, clustering, and basic neural network models.

most of the code for the algorithms in scratch

I'm trying to rebuild the machine learning model from scratch

Introduction To Classification Algorithms in Machine Learning

🤖 This repository contains the codes written to build the primitive machine learning models from scratch 👨🏽‍💻

Car Price Prediction Machine Learning

This repository has the implementation of various Machine Learning algorithms by only using native Python with numpy

House Price Prediction

Machine Learning course tasks focused on the implementation of the ML algorithms using libraries such as Numpy, Pandas, etc.

In this repository you can find the examples of Logistic Regression , K-NN, Decision Tree, Random Forest algorithms.

In this project, the best model is searched to predict a subscription plan for a telco's customers.

To detect whether the person will suffer from chronic kidney disease or not using Machine learning algorithm

This is to practice the machine learning algorithms mentioned in the book.

Machine Learning with Python Libraries

To predict the probability of survival of people who embark on a journey in the Titanic ship. The dataset consists of important features which were to be learnt such as Passenger class, Age, Sugar condition, Physical Injury, etc.The target feature is to predict is the Survival probability whose value is either 1 (can survive) or 0 (cannot survive).

This repo is developed as a course portfolio for the graduate class "INDE 577 - Data Science and Machine Learning" at Rice University, Sping 2023.

Implementation of some machine learning algorithms in Python.

Projects on Machine learning using classification and regression techniques

Machine Learning using K-Nearest Neighbors Algorithm