Karma of Humans is AI

Machine Learning Notebooks for various Algorithms with data file

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.

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

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

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.

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.

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.

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

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.

Classification Machine Learning project

This Jupyter Notebook serves as a cardiovascular disease (CVD) prediction model developed using Python and popular data analysis libraries such as Pandas, Numpy, and Seaborn. The model takes input as patient's symptoms and utilizes the K-Nearest Neighbors algorithm to predict whether the person is likely to have cardiovascular disease or not.

Jupyter Notebooks exploring Machine Learning techniques -- regression, classification (K-nearest neighbour (KNN), Decision Trees, Logistic regression vs Linear regression, Support Vector Machine), clustering (k-means, Hierarchical Clustering, DBSCAN), sci-kit learn and SciPy -- and where it applies to the real world, including cancer detection, …