mohdghazanfar Goto Github PK

ai-based-network-intrusion-detection-system

This repository contains code for building a machine learning model for intrusion detection using a network traffic dataset. It involves data preprocessing, feature engineering, ensemble model training and evaluation.

debiasurdunlp

This repository contains code for mitigating gender biases in Urdu word embeddings. It offers algorithm for identifying biases, algorithms for debiasing, and evaluation metrics to assess effectiveness. Designed for researchers and developers, it aims to promote fairness in NLP applications.

genetic-algorithm-binary-optimization

This repository contains code implementation of a simple genetic algorithm for solving a binary optimization problem.

hyperopt-sklearn

Hyper-parameter optimization for sklearn

mlp-depth-hypothesis-experiment

This repository contains a program testing the depth hypothesis on a Multi-Layer Perceptron (MLP) neural network.

mohdghazanfar

Config files for my GitHub profile.

mysql-mongodb

This repository contains a collection of MySQL queries and MongoDB commands, organized by component.

nlp-essentials

This repository contains code for learning NLP through practical examples using NLTK and spaCy. It includes Jupyter notebooks covering basic to advanced NLP techniques, ideal for beginners and intermediate learners. From text processing to building chatbots, this collection is a straightforward path to understanding and applying NLP concepts.

parking-reservation-system

This repository contains a parking reservation system implemented in C++ using object-oriented programming concepts.

readmebox

supervised-learning-knn-dtc

This repository contains code for KNN and decision tree classifiers with entropy and gini criteria. Built from scratch or using scikit-learn library. Evaluates accuracy with iris dataset, compares classifier performance, visualizes decision trees and feature importance.

unsupervised-learning-k-means-clustering

This repository contains code for Customer Segmentation using K-means Clustering.