Brenda Chepkoech's Projects
Fraud Detection in Electricity and Gas Consumption Challenge. Help Tunisian company STEG detect fraud
30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace.
ADS offers a friendly user interface, with objects and methods that cover all the steps involved in the lifecycle of machine learning models, from data acquisition to model evaluation and interpretation. Requires: Python >= 3.7, < 3.10
As a Data Science Consultant help a Kenyan Entrepreneur identify which individuals are most likely to click on her ads for an advert on her blog.
anomaly-detection-challenge
This repository contains a project that investigates a claim about the blue cars from the provided Autolib dataset.
The goal of the problem is to predict whether a client will default on the vehicle loan payment or not. For each ID in the Test_Dataset, you must predict the βDefaultβ level.
Config files for my GitHub profile.
With the help of this dataset, one can understand more about human sentiments in text and analyze the context and language when a user intends to make/post a hatred/racist comment(s)
Python with Machine Learning Course done by Coding Black Females
Data science interview questions with answers. Not ideally (yet)
This repository contains codes of my submission for DSA questions.
Data Structures and Algorithms(DSA)
Keep track of the self-learning progress of useful data science tools
The project focuses on processing stations data to understand electric car usage over time
Building face mask detector with Convolutional Neural Network.
The project focuses on assessing the level of financial inclusion in the region encompassing Kenya, Rwanda, Uganda, and Tanzania.
A model for predicting which individuals are most likely to have or use a bank account as it will help provide an indication of the state of financial inclusion in East Africa.
Lux Academy & Data Science East Africa Python Boot Camp, Building and Deploying Flask Application Using Docker Demo App.
Building different regression models that would allow Hass Consult company to accurately predict the sale of prices and advice on the best Model to use.
Python code to detect hate speech and classify twitter texts using NLP techniques and Machine Learning
Created for Moringa Prep, to demonstrate forking repositories.
Example of deploying a Python Flask app onto Heroku
Building a model that determines whether or not the patient's symptoms indicate that the patient has hypothyroid.
Implementation of K-nearest neighbor (kNN) classifier to predict whether a person will survive in the Titanic Survival dataset and a Naive Bayes classifier to classify an email whether it is spam or not.