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lynseybwisa/README.md

Lynsey Bwisa - Machine Learning and Data Science Enthusiast πŸ‘©β€πŸ’»

Hello there! πŸ‘‹ Welcome to my GitHub profile. I'm Lynsey Bwisa, and I'm passionate about all things Machine Learning and Data Science. I'm constantly exploring, learning, and building exciting projects in this fascinating field.

About Me 🧐

I'm a data enthusiast with a background in computer science and a deep curiosity for how data can be harnessed to solve real-world problems. My journey in Machine Learning began with an eagerness to understand the algorithms that power artificial intelligence and how they can transform industries and people's lives.

Interests πŸ’‘

  • Machine Learning Algorithms: Delving into the world of neural networks, decision trees, support vector machines, and more, is like exploring a universe of possibilities. I love experimenting with various ML algorithms to understand their strengths and weaknesses.

  • Data Visualization: Unleashing the power of data visualization tools to tell compelling stories from complex datasets is a true art. I enjoy creating captivating visualizations that make data more accessible and insightful.

  • Natural Language Processing (NLP): The ability to teach machines to understand and interpret human language is incredible. I'm captivated by NLP and its potential to revolutionize how we interact with technology.

  • Big Data and Analytics: Analyzing vast amounts of data to extract valuable insights is both challenging and rewarding. I'm enthusiastic about diving deep into big data challenges and finding actionable patterns.

Projects πŸš€

Here are some of the exciting projects I've been working on:

  • Spotify Dataset EDA: Explored and analyzed a rich dataset from Spotify, uncovering interesting patterns and insights about music preferences and user behavior.

  • Airlines Dataset EDA: Conducted an in-depth exploratory data analysis on a comprehensive airlines dataset, gaining valuable insights into flight patterns, delays, and passenger trends.

  • End-to-End ML Project - Predicting Student Performance: Developed a complete Machine Learning pipeline for analyzing, modeling, and predicting student performance based on various academic and socio-economic factors, providing valuable early intervention insights for educators.

  • Predicting House Prices: Implemented a mini Machine Learning project to predict house prices using regression techniques, enabling potential homebuyers and sellers to make informed decisions.

Get in Touch πŸ“¬

I'm always open to collaborating on exciting ML and data science projects. If you have any ideas or just want to connect, feel free to reach out to me via email at Email or find me on LinkedIn

Let's harness the power of data together and make an impact on the world! 🌍✨

Pinned

  1. british-airways-sentiment-analysis british-airways-sentiment-analysis Public

    Jupyter Notebook

  2. iris-flower-classification iris-flower-classification Public

    Jupyter Notebook

  3. KPMG-Sprocket-Data-Quality-Analysis KPMG-Sprocket-Data-Quality-Analysis Public

    The project is dedicated to assessing and enhancing the quality of data provided by Sprocket Central Pty Ltd.

    Jupyter Notebook

  4. ml-project ml-project Public

    This repository demonstrates an end to end Machine Learning project

    Jupyter Notebook

  5. Spotify-Playlist-EDA Spotify-Playlist-EDA Public

    This repository does exploratory data analysis on Spotify dataset

    Jupyter Notebook

  6. IBM-Machine-Learning IBM-Machine-Learning Public

    This is a repository with all my Machine Learning mini-projects

    Jupyter Notebook