Brian Mburu's repositories
Cockoo-Search-Algorithm
Cuckoo Search Algorithm implementation in Python
Analysis-on-panel-data
comprehensive analysis of panel data
Brain-Tumor-Identification-and-Localization
This project uses deep learning to detect and localize brain tumors from MRI scans. It uses a ResNet50 model for classification and a ResUNet model for segmentation. It evaluates the models on a dataset of LGG brain tumors.
Distiled-BERT-model-training-pytorch
A noote book to showcases training the Distilled Bert model on Toxic Comment Dataset.
Market_Segmentation
Notebook to Perform Market Segmentation using K-means clustering, PCA, and Auto-encoders.
Queuing-Theory-Simulation
Simple script to Simulate Customer waiting to be served in a server using Queuing Theory.
Artificial-Bee-Colony-in-python
Artificial Bee Colony algorithm implementation in python.
Bouncing-Ball-simulation
Simple Script to simulate a ball falling from a height.
KDTree-based-K-Nearest-Neighbor-Graph
KDTree-based K-Nearest Neighbor graph implementation using python
Kernighan-Lin-Algorithm
Kernighan-Lin Algorithm implementation in python. Kernighan-Lin Algorithm is a graph partitioning algorithm that optimizes the cut size between two subsets of nodes.
Multi-Probe-LSH
Multi-Probe LSH implementation in python using annoy library.
Nearest-Neighbour-Descent--HNSW-Algorithm-
NN-Descent Implementation in python using the nmslib library
Qualitative-Dependent-Linear-Models
A notebook to analyze the performance between three Qualitative Dependent Linear Models when fitted on the diabetes dataset
seleneum-simple-web-scrapper
Simple project to perform simple data analysis on data scrapped from the web using Beautifulsoup and Selenium webdriver.
Student-Registration-system-in-java-using-javafx
This is a java project in Student Registartion System. This system used SQLITE database and GUI is created in javafx
Student_site
A platform to develop your career
Toxic-Comment-Classification-App
Toxic comment classification REST API using FastAPI and PyTorch. Accepts text input, returns toxicity predictions.
Toxic-Comment-Explanatory-Data-Analysis
This notebook analyzes a dataset of toxic comments using NLP techniques such as stemming/lemmatizing, exploratory data analysis, and DistilBERT classification. The goal is to identify patterns and relationships between the features and the target variable, as well as to build a model for classifying toxic comments.