<feed xmlns="http://www.w3.org/2005/Atom"> <id>https://muhuyierick.github.io/</id><title>Muhuyi Erick</title><subtitle>My Data Science | Data Analysis | ML | AI | DL | Statistics.</subtitle> <updated>2025-11-20T14:53:52+03:00</updated> <author> <name>Muhuyi Erick</name> <uri>https://muhuyierick.github.io/</uri> </author><link rel="self" type="application/atom+xml" href="https://muhuyierick.github.io/feed.xml"/><link rel="alternate" type="text/html" hreflang="en" href="https://muhuyierick.github.io/"/> <generator uri="https://jekyllrb.com/" version="4.4.1">Jekyll</generator> <rights> © 2025 Muhuyi Erick </rights> <icon>/assets/img/favicons/favicon.ico</icon> <logo>/assets/img/favicons/favicon-96x96.png</logo> <entry><title>Deep Learning Project: Handwritten Digit Recognition with Neural Networks</title><link href="https://muhuyierick.github.io/posts/Deep-Learning/" rel="alternate" type="text/html" title="Deep Learning Project: Handwritten Digit Recognition with Neural Networks" /><published>2025-11-20T00:00:00+03:00</published> <updated>2025-11-20T14:53:33+03:00</updated> <id>https://muhuyierick.github.io/posts/Deep-Learning/</id> <content type="text/html" src="https://muhuyierick.github.io/posts/Deep-Learning/" /> <author> <name>Muhuyi Erick</name> </author> <category term="deep-learning" /> <category term="neural-networks" /> <category term="python" /> <category term="computer-vision" /> <summary>Introduction I completed a comprehensive deep learning project focused on building and training an Artificial Neural Network (ANN) for handwritten digit recognition using the famous Modified National Institute of Standards and Technology (MNIST) dataset. This project provided me with hands-on experience in designing, implementing, and evaluating neural networks using TensorFlow and Keras, while...</summary> </entry> <entry><title>Machine Learning Operations (MLOPs) Project: Housing Price Prediction Pipeline</title><link href="https://muhuyierick.github.io/posts/MLOPs/" rel="alternate" type="text/html" title="Machine Learning Operations (MLOPs) Project: Housing Price Prediction Pipeline" /><published>2025-11-19T00:00:00+03:00</published> <updated>2025-11-19T00:00:00+03:00</updated> <id>https://muhuyierick.github.io/posts/MLOPs/</id> <content type="text/html" src="https://muhuyierick.github.io/posts/MLOPs/" /> <author> <name>Muhuyi Erick</name> </author> <category term="mlops" /> <category term="machine-learning" /> <category term="python" /> <category term="deployment" /> <summary>Introduction I completed a comprehensive MLOps project focused on building a complete machine learning pipeline for predicting California housing prices. This project took me through the entire machine learning lifecycle - from data preprocessing and model training to hyperparameter tuning, evaluation, and finally deployment as a web service. The experience provided me with practical MLOps skil...</summary> </entry> <entry><title>Classification Models in Python</title><link href="https://muhuyierick.github.io/posts/Classification-Models/" rel="alternate" type="text/html" title="Classification Models in Python" /><published>2025-11-10T00:00:00+03:00</published> <updated>2025-11-10T18:36:15+03:00</updated> <id>https://muhuyierick.github.io/posts/Classification-Models/</id> <content type="text/html" src="https://muhuyierick.github.io/posts/Classification-Models/" /> <author> <name>Muhuyi Erick</name> </author> <category term="machine-learning" /> <category term="classification" /> <category term="python" /> <category term="data-exploration" /> <category term="data-modelling" /> <summary>Introduction As part of my Data and AI journey with Cyber Shujaa, I completed a comprehensive classification modeling project focused on predicting wine categories based on chemical properties. This project provided me with hands-on experience in building, evaluating, and comparing multiple classification algorithms using Python’s scikit-learn library. The experience deepened my understanding ...</summary> </entry> <entry><title>Regression Modeling in Python</title><link href="https://muhuyierick.github.io/posts/Regression-Model-in-Python/" rel="alternate" type="text/html" title="Regression Modeling in Python" /><published>2025-10-31T00:00:00+03:00</published> <updated>2025-11-02T08:23:22+03:00</updated> <id>https://muhuyierick.github.io/posts/Regression-Model-in-Python/</id> <content type="text/html" src="https://muhuyierick.github.io/posts/Regression-Model-in-Python/" /> <author> <name>Muhuyi Erick</name> </author> <category term="regression-modeling" /> <category term="python" /> <category term="data-exploration" /> <category term="data-cleaning" /> <summary>Introduction The goal of this project was to build a simple linear regression model that predicts home prices from the house area. I started with three CSV files containing small example datasets. I read these files into pandas DataFrames, inspected their structure and contents, and then decided which dataset was most suitable for a single-feature linear regression. After selecting the dataset...</summary> </entry> <entry><title>Data Visualization In Tableau</title><link href="https://muhuyierick.github.io/posts/Data-Visualization-in-Tableau/" rel="alternate" type="text/html" title="Data Visualization In Tableau" /><published>2025-10-20T00:00:00+03:00</published> <updated>2025-10-20T00:00:00+03:00</updated> <id>https://muhuyierick.github.io/posts/Data-Visualization-in-Tableau/</id> <content type="text/html" src="https://muhuyierick.github.io/posts/Data-Visualization-in-Tableau/" /> <author> <name>Muhuyi Erick</name> </author> <summary></summary> </entry> </feed>
