Python is the most widely used language in machine learning because it is readable and has excellent libraries. You do not need a computer science degree to start.
Step 1: Python basics
Variables, lists, dictionaries, loops, functions and reading files. Aim to write small scripts that solve everyday problems.
Step 2: Working with data
- NumPy for fast numerical work.
- pandas for tables of data: cleaning, filtering, grouping.
- Matplotlib or seaborn for charts.
Step 3: Your first models
scikit-learn makes classic machine learning approachable: linear regression, decision trees and clustering. Learn to split data into training and test sets and to measure accuracy honestly.
Step 4: Deep learning
Once the basics feel comfortable, move on to PyTorch or TensorFlow to build neural networks for images and text.
Tips
- Use Jupyter notebooks to experiment.
- Practise on public datasets.
- Code a little every day rather than a lot once a week.