Munyala Eliud - Data Engineer & Machine Learning Nairobi,Kenya

Data Science 👨‍🔬 | Statistics 📊 | Machine Learning 🤖

Follow me on linkedIn

[https://www.linkedin.com/in/eliud-munyala/]

My email

[meamunyala@gmail.com]

Folder Structure

0_Programming_Intro_R_Python 🐍

• Introduction to Python and R programming.

1_Statistics 📊

• Statistics using python

2_SQL Scripting🧾

• Various notebooks related to SQL basics and operations.

• Other statistical notebooks covering topics like Bayes Theorem, Distribution Analysis, Sampling methods, and more.

3_Machine_Learning 🤖

• Notebooks covering machine learning algorithms and techniques, including Support Vector Machines, Decision Trees, Regression models, etc.

4_Deep_Learning 🤖

• Notebooks and projects related to deep learning, including computer vision, natural language processing, neural networks, and TensorFlow.

5_E2E_projects 🏗️

• Various end-to-end projects, including data cleaning, analysis, and specific project-related notebooks. DataViz_Storytelling

Interview-pendahealth

• Notebooks and data related to a BI Analyst technical interview.

Kaggle-Competition

ImagingDetection-2022-Closed.ipynb

• Notebook related to a closed Kaggle competition on imaging detection in 2022.

code_snippets.ipynb

• Notebook containing code snippets.

File listing dependencies for running the code.

• requirements.txt

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Feel free to explore the folders and notebooks based on your interests and learning objectives. Each folder may contain its own README or specific instructions on how to use or run the code within.

Contributing

If you'd like to contribute to this repository, feel free to create a pull request or raise an issue. Contributions are welcome!

License

This repository is licensed under the MIT License.