Machine Learning Engineer Certification Projects

Welcome to the Machine Learning Engineer Certification Projects repository! Here, you will find a collection of pilot projects and the final capstone project that were completed during my journey to become a certified Machine Learning Engineer. The projects are organized into week-by-week folders, each containing Google Colab notebooks or Python files that showcase the work accomplished during that particular week. Additionally, data used in these projects can be found in subfolders appropriately named "data."

Please note that this repository is a work in progress, and files are continually being uploaded to provide a comprehensive overview of the projects and the skills developed throughout the certification program. Feel free to explore the folders and files to gain insights into the various machine learning topics covered during the course.

Table of Contents

• Project Structure
• Getting Started
• Week 1: Medical Cost Prediction (Scikit-learn Models)
• Week 2: Smoker Status Prediction (Scikit-learn Models)
• Week 3: Gaussian Naive Bayes Classifier (From Scratch)
• Week 4: Smoker Status Prediction (Data Balancing, Hyperparameter Tuning, and Regularization)
• Week 6: Stroke Prediction (Dense Neural Networks and Data Pipeline)
• Week 7: Mask Detection (Convolutional Neural Networks)
• Week 8: Machine Translation (RNNs, LSTMs, GRUs, Embeddings)
• Week 10: Deployment (Flask, Docker, and Gradio)
• Week 12 to 16: Capstone Project (Talent Recommendation Engine using OpenAI)

Project Structure

The repository is structured as follows:

• Week X: Each week is represented by a separate folder (e.g., Week 1, Week 2, etc.). Inside each week's folder, you'll find project-specific materials, code, and documentation.

• data: This subfolder contains the datasets used in the projects. You can explore the data to better understand the context and the challenges addressed in each project.

Contact Information

If you have any questions or would like to get in touch, you can reach me at royaad@live.com. Thank you for visiting this repository, and I hope you find the projects insightful and valuable in your journey to becoming a machine learning expert.