A while back, I wanted to host a blog that allowed me to bring the content I find the most useful but also very interesting new concepts and methods of performing tasks in newer, more efficient ways.
I am a Machine Learning Engineer with a strong mathematical background and over two years of experience in software development, data engineering, and deploying and maintaining solutions in production. I specialize in utilizing Machine Learning, Computer Vision, and NLP models to create algorithms that provide valuable insights by analyzing data from ETL pipelines. With expertise in time-series analysis, anomaly detection, statistical learning, and deep learning, I have a track record of delivering high-quality projects that meet business requirements.
I hold a Bachelor's degree in Computational Mathematics from Jomo Kenyatta University and I am currently pursuing a Master's degree in Computer Science at the University of East London. In my Master's program, I have taken advanced coursework in Big Data Analytics, Artificial Intelligence and Machine Vision, Cloud Computing, and Advanced Software Engineering.
I have expertise in a wide range of technical skills, including time-series analysis, anomaly detection, NLP, deep learning, statistical learning, and deployment frameworks like Flask, Django, Streamlit, and MLflow. I am also skilled in data engineering tools like Apache Kafka, Airflow, Airbyte, DVC, and Apache Spark. In addition, I am proficient in AWS services like EC2, Lambda, S3, CloudWatch, Athena, Redshift, and Kinesis, as well as Relational Databases like MySQL, SQLServer, Oracle, and NoSQL databases like ElasticSearch and DynamoDB. I am experienced in object-oriented development using Python and Java.
In addition to my technical skills, I possess excellent soft skills such as communication, problem-solving, and decision-making. I am a team player who enjoys collaborating with others and sharing my knowledge to achieve common goals.
I currently work as a Machine Learning Engineer at Kunumi in Brazil, where I am developing a process-oriented data platform and an automatic prediction engine to help businesses save billions by answering questions from data. Prior to that, I worked as a Lead Machine Learning Engineer at Omdena in San Diego, where I created a hybrid model of computer vision and NLP techniques to perform near-accurate data extraction. I also led a team in creating the Dagshub plus DVC data pipelines and designed the deployment and packaging of the project. In addition, I worked on building a Knowledge Graph of land ownership in Kenya and developed a Named Entity Recognition model for entity identification from gazettes and court documents.
I have worked on several exciting projects, including the creation of a Fake Reviews Detector, where I trained machine learning models to classify reviews as fake or real. The project takes in a URL to the reviews of the product, and then it crawls all the reviews and classifies them!
In my spare time, I mentor learners as an Associate Cloud Engineer (GCP) for Google Africa Developer scholarship, where I guide and unblock them while engaging with the content and assigned projects.
Overall, I am a passionate and skilled Machine Learning Engineer who is committed to delivering high-quality projects that meet business requirements. I am excited about exploring new technologies, collaborating with others, and making an impact in the field of data engineering and machine learning.