Implementasi algoritma kNN dengan Python

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.

Exploring Federated Learning with TensorFlow, torch and Pysyft

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

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

👥 ➡️ 💰 Analysis and classification model for the adult dataset

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

Census income prediction by employing the power of supervised learning

Analysis and classification of annual income of an individual on 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

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

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

Naive Bayes

A PYTHON3, HTTPS SERVER WITH USERNAME AND PASSWORD PROTECTION

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.

TOKI-BOT, the friendly code-generator for fledgling open-source data producers

Visualising Accuracy vs. Fairness in ML models using AIF360 tools and dataset

To Determine the probability of a person to earn greater than 50,000 USD based on the features on the census dataset