Machine Learning Journey Repository 🚀

Welcome to my Machine Learning Journey Repository! This repository contains comprehensive resources, hands-on projects, and code from advanced machine learning courses/programs:

• DeepTech_Ready Upskilling Programme – by 3MTT and Data Science Nigeria(DSN).
• TensorFlow Developer Course – by Zero to Mastery.
• Machine Learning Mastery – by Andrei Neagoie and Daniel Bourke.

Whether you're a beginner or an experienced developer, this repository will help you dive deep into machine learning.

📂 Directory Structure:

│── deeptech_program_cohort1/               # DeepTech_Ready Upskilling Programme
│
│── tensorflow_course/               # TensorFlow Developer Course (Zero to Mastery)
│    ├── 00_tensorflow_fundamentals.ipynb  # Fundamentals of TensorFlow (Colab Notebook)
     ├── 01_neural_network_regression_with_tensorflow.ipynb # Neural Network Regression with TensorFlow
     |--- 02_neural_network_classificaton_with_tensorflow.ipynb
     |--- 03_introduction_to_computer_vision_with_tensorflow.ipynb
│   └── README.md                         # Course-specific details
│
├── zero-to-mastery_ml/                      # Machine Learning Mastery Course (Andrei Neagoie & Daniel Bourke)
   ├── .ipynb_checkpoints/          # Jupyter Notebook checkpoints
   ├── matplotlib/                  # Notebooks and projects using Matplotlib
   ├── numpy/                       # Numpy tutorials and exercises
   ├── pandas/                      # Data manipulation with Pandas
   ├── projects/                    # Machine learning projects and case studies
   ├── scikit-learn/                # Notebooks focused on using Scikit-learn
   ├── car-sales.csv                # Dataset: Car sales data for analysis
   ├── heart-disease.csv            # Dataset: Heart disease data for model training
   ├── heart_disease_analysis_plot.png # Visualization output from analysis
   ├── introduction_to_numpy.ipynb  # Introduction to Numpy Notebook
   ├── cd/                          # Additional files related to the course
   ├── .gitignore                   # Files and directories to be ignored by Git
   └── README.md                    # Course-specific details