In this, i carried out EDA(exploratory data analysis) on adult_data.csv to extract meaningful insights and followed it by applying LogRegression on it.

Naive Bayes and Decision Tree Classifiers implemented with Scikit-Learn and Graphviz visualization (Datasets - News, Mushroom, Income)

Implementasi algoritma kNN dengan Python

Classification Adult DataSet (https://archive.ics.uci.edu/ml/datasets/Adult) using MLP (Multi-Layer Perceptron).

Census income prediction by employing the power of supervised learning

Exploring Federated Learning with TensorFlow, torch and Pysyft

Boosting Implementation (Ada-Boosting, Gradient Boosting, XGB)

👥 ➡️ 💰 Analysis and classification model for the adult dataset

Decision tree, Adaboost, KNN, Naive bayes, PCA, EM algorithm assignments of Machine Learning Sessional Course CSE 472 in Level-4, Term-2 of CSE, BUET

DT-id3classifier that can fit with categorical values

Analysis and classification of annual income of an individual on Adult dataset

Intro to Machine Learning Assignment 3

Project for Artificial Intelligence exam: Pruning of the Decision Tree rules

A PYTHON3, HTTPS SERVER WITH USERNAME AND PASSWORD PROTECTION

Implementação de um KNN para predição no dataset Adult. Projeto feito como EP da disciplina de Aprendizado de Máquina na POLI-USP.

Project aimed to compare performance of standard Machine Learning algorithms on a Person Income Prediction problem

Naive Bayes

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This project investigates factors influencing income using the Adult Income Dataset. It involves data preprocessing, visualization, and machine learning. Key steps include data cleaning, feature transformation and engineering. Predictive models are developed to classify income levels, providing insights into key determinants.