Karma of Humans is AI

Machine Learning Notebooks for various Algorithms with data file

Implementing machine learning algorithms while learning them.

This notebook consists of the notebook file that consists of a supervised learning model built to classify the nature of the breast cancer cells based on the features.

Notebooks explaining various Machine Learning concepts.

This is GEM repo, as it has all the Hands-On ML notebooks

This notebook can be used to quickly revise the KNN algorithm.

All Possible Machine Learning algorithms implementation in jupyter notebook with csv file.

This project deals with implementation of various machine learning models from scratch in python( jupyter notebook) without actually importing them from the sklearn library.

In this notebook we'll see how to use KNN to classify the IRIS Flowers.

A raw implementation of K Nearest Neighbours (KNN) in Python.

A notebook aimed to predict loan eligibility with high accuracy using advanced machine learning models including Logistic Regression and KNN.

Loan Eligibility Prediction Model: A machine learning application to predict loan approval based on applicant data. Includes a web interface for submitting loan applications and receiving predictions. Built with Python and Jupyter Notebook.

my first projectWelcome to my second DS project also my first notebook on kaggle. In this notebook, I explore the Breast Cancer dataset and develop an RF model to try classifying suspected cells as Benign or Malignant. after using K-fold cross-validation with logistic regression, RF, SVM, and KNN to check the best model for my dataset.

Welcome to my second DS project also my first notebook on kaggle. In this notebook, I explore the Breast Cancer dataset and develop an RF model to try classifying suspected cells as Benign or Malignant. after using K-fold cross-validation with logistic regression, RF, SVM, and KNN to check the best model for my dataset.

This notebook leverages publicly available heart disease patient data to train several machine learning models for accurately diagnosing heart disease. Uses shapley values to explain ML models.

Python based Jupyter Notebook Project to Predict Potential Customer for Term Deposit Marketing Campaign in Banking Institution using Logistic Regression, K-NN, Decision Tree & Random Forest Supervised Classification Machine Learning

Classification Machine Learning project

This notebook demonstrates the basic application of two common machine learning algorithms, KNN and Decision Tree, for species classification using the classic Iris dataset. This is a beginner-friendly guide for understanding and applying basic classification techniques in Python using scikit-learn.