Getting Started with Machine Learning
- 1. Learn the basics of Python and libraries like NumPy and Pandas.
- 2. Understand statistics and linear algebra fundamentals.
- 3. Explore key concepts: supervised learning, unsupervised learning, regression, and classification.
- 4. Use scikit-learn for simple machine learning models.
- 5. Practice with datasets from Kaggle or UCI ML Repository.
- 6. Progress to advanced tools like TensorFlow and PyTorch.
Getting Started with Machine Learning