This repository contains a Jupyter Notebook exploring the adult income dataset. The notebook performs Exploratory Data Analysis (EDA), including visualizations with charts and graphs. Additionally, it implements various classification models to predict income and analyzes their accuracy.

Educational notebooks reviewing machine learning models and concepts.

This notebook explores fraud detection using various machine learning techniques.

Basics of machine learning is END-TO-END Repository which includes very Basic Machine Learning Models and Notebook

Jupyter notebook for the "10-year Coronary Heart Disease (CHD) risk from the Framingham Heart study dataset" project (part of the course in Machine Learning)

Predictive analysis using logistic regression to determine college admissions based on CET scores. This project includes detailed steps for data preparation, model training, and evaluation using Python and scikit-learn in a Jupyter Notebook environment.

Implementation of Logistic Regression from scratch to predict the sex of penguin based on species, island and age using Python, Jupyer Notebook, Numpy, Pandas, Matplotlib

Master Decision Trees & Ensembles in Python with this ML notebook! Classification, Regression, Bagging, Boosting, & Tuning. Elevate your ML skills now! 🌲🚀

Several notebooks that cover various ML concepts such LR, CNN's, RNN's, & more!

This Repository is all about the popular Artificial Intelligence Lab concepts and their variations. Which can be helpful to Machine learning. I have try Artificial Intelligence Lab all problems solutions using prolog, python Programming Language and Jupyter Notebook program.

Juyter Notebook for classification of fraudulent or legal credit card transactions

This repository is made following the course by Sir Jose Portilla, and focuses on Supervised Machine Learning algorithms. I studied all these concepts in December 2023

Interactive exploration of logistic regression, multinomial classification, and transfer learning using Python and Jupyter Notebooks in the context of data science education.

A series of 12 assignments/labs regarding Stochastic Processes and Machine Learning including a plethora of models and techniques implemented in Google Colab notebooks

The notebook contains Python code for various machine learning tasks and models. Here is an overview of its content:

This repository contains a single notebook, notebook.ipynb, which analyzes the ability of three machine learning algoithms — Multinomial Naive Bayes, Logistic Regression, and Support Vector Machine — to determine whether customer reviews of the Disneyland amusement park in California are positive or negative.

This repository houses Python implementations of foundational machine learning algorithms.Each algorithm file or Jupyter Notebook demonstrates the application, functionality, and usage of these algorithms in Python.

This repository hosts a Jupyter notebook for Fake News Detection, utilizing machine learning algorithms like Logistic Regression , Gradient Boosting Classifier , Random Forest and Decision Tree. The project covers data preprocessing, analysis and manual testing of news articles, with added multi language support using Google Translate API .

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