James Wainaina Githirwa | Data Scientist

James Wainaina Githirwa

Data Scientist

Based in Nairobi

About

James Githirwa is an ambitious junior Data Scientist having pursued studies in the fields of Data Science at ALX Africa. He is passionate about Data Science and Machine Learning. He is equipped with the practical skills to guide an organization and its employees through times of change. His personal mantra “Try and become 1% better every day”, gives him the motivation to keep working on improving himself everyday without any self-doubt in the work he has done. He embraces hard and challenging tasks wholeheartedly and he always comes out on top.

Skills

Projects

Book recommender system

This group project implements a content-based filtering recommendation system that suggests books based on user preferences. The system utilizes the Goodbooks-10k dataset, which contains information on 10,000 books and approximately 80,000 reviews.

Earthquake Damage Predictor

This project aims to predict the damage caused by earthquakes in the Gorkha district of Nepal. Using a dataset containing various features related to buildings, the model evaluates the likelihood of severe damage during an earthquake.

Covid-19 Virus Infection Prediction

This project focuses on building a Machine Learning model to predict the chances of contracting the COVID-19 virus using a dataset of possible symptoms. The model is designed to take symptoms as input and predict whether COVID-19 is likely present.

Fake News Detector

The Fake News Detector project focuses on building a machine learning model to detect fake news articles. The model utilizes natural language processing techniques and machine learning algorithms to classify news articles as either "Fake" or "Real"

Validating our data

In this project I am diving into the agricultural dataset again to continue to validate our data. First I build a data pipeline that will ingest and clean our data with the press of a button, cleaning up our code significantly. I also perform hypothesis testing to determine if our dataset is a repre

Decision Tree exercise

This project is an exercise to implement a Decision Tree model for classification tasks. The model is trained on a dataset and evaluated for its accuracy in making predictions. I will be using an agriculture dataset to explore the effect climate change has on crops in Maji Ndogo. Below is the data

SQL Exam

An exam on a movie database executing SQL queries to solve a problem.

Clustering data to unveil Maji Ndogo's water crisis

Water Accessibility and infrastructure summary report. This survey aimed to identify the water sources people use and determine both the total and average number of users for each source. Additionally, it examined the duration citizens typically spend in queues to access water.