Welcome to my Machine Learning Journey!
This repository documents my daily learning progress as I build a strong foundation in Machine Learning, Artificial Intelligence, and Data Science through hands-on learning, projects, and continuous practice.
Hi, I'm Rehana Hassan.
I'm a Software Engineering student and Data Analyst transitioning into Machine Learning and Artificial Intelligence.
My goal is to become an AI & Machine Learning Engineer by mastering machine learning concepts, building real-world projects, and continuously improving my technical skills.
This repository serves as my public learning journal throughout the Machine Learning Specialization by DeepLearning.AI.
Here you'll find:
- 📖 Daily learning notes
- 🧠 Concepts explained in simple language
- 💻 Hands-on practice
- 🚀 Machine Learning projects
- 📊 Progress tracking
- 🏆 Course milestones and certificates
- 💡 Personal reflections
- Build a strong Machine Learning foundation
- Master Supervised and Unsupervised Learning
- Learn Neural Networks and Deep Learning
- Build practical Machine Learning projects
- Learn Model Deployment and MLOps
- Become an AI & Machine Learning Engineer
machine-learning-journey/
│
├── course-01/
│ ├── Day-01/
│ ├── Day-02/
│ ├── ...
│ └── Day-06/
│
├── course-02/
│ ├── Day-01/
│ ├── Day-02/
│ ├── ...
│ └── Day-14/
│
├── course-03/
│ └── (Coming Soon)
│
├── milestones/
│ ├──course-1-completed
│ ├──course-1-completed
│
├── certificates/
│ ├── course-01-certificate.png
│ └── course-02-certificate.png
│
└── README.md
Each day contains my notes, summaries, achievements, and reflections from the lessons I complete.
Supervised Machine Learning: Regression and Classification
Topics learned:
- Linear Regression
- Multiple Linear Regression
- Gradient Descent
- Feature Scaling
- Feature Engineering
- Polynomial Regression
- Logistic Regression
- Classification
- Decision Boundaries
- Logistic Loss
- Cost Functions
🏆 Certificate Earned
Advanced Learning Algorithms
Topics learned:
- Neural Networks
- Forward Propagation
- TensorFlow
- Activation Functions (Sigmoid, ReLU, Softmax)
- Binary & Multiclass Classification
- Model Evaluation
- Cross Validation
- Bias and Variance
- Learning Curves
- Regularization
- Decision Trees
- Random Forest
- XGBoost
- Tree Ensembles
- Error Analysis
- Transfer Learning
- Fairness and Ethics
🏆 Certificate Earned
| Course | Status |
|---|---|
| ✅ Course 1 – Supervised Machine Learning | Completed |
| ✅ Course 2 – Advanced Learning Algorithms | Completed |
| 🚀 Course 3 – Unsupervised Learning, Recommenders & Reinforcement Learning | Starting Soon |
Alongside my coursework, I'm building practical Machine Learning projects to strengthen my understanding.
Current projects include:
- 🏠 House Price Prediction
- 📚 Student Score Prediction
- 🎓 Pass/Fail Classifier
More projects will be added as I continue learning.
- Python
- NumPy
- Pandas
- Matplotlib
- Scikit-learn
- TensorFlow
- Jupyter Notebook
- SQL
- Power BI
- Git & GitHub
I believe in:
- Learning consistently
- Practicing every day
- Writing clear notes
- Building real projects
- Sharing my progress publicly
Small improvements every day lead to remarkable results.
- Complete Course 3 of the Machine Learning Specialization
- Build 20+ Machine Learning projects
- Learn Deep Learning
- Learn MLOps and Model Deployment
- Build AI-powered applications
- Contribute to Open Source AI projects
https://www.linkedin.com/in/rehana-hassan/
⭐ Thank you for visiting my repository!
If you're also learning Machine Learning, feel free to explore my notes, follow my journey, or connect with me.
Happy Learning! 🚀