Machine learning is one of the fastest-growing fields in technology today, and beginners often struggle with knowing where to start.
In this post, we’ll walk through a practical roadmap:
Understand the Basics – Learn about supervised and unsupervised learning, classification, and regression.
Choose a Programming Language – Python is highly recommended due to its rich ecosystem of libraries like NumPy, Pandas, Scikit-learn, and TensorFlow.
Build Small Projects – Start with simple projects like predicting house prices or classifying images.
Work with Real Data – Use datasets from Kaggle, UCI Machine Learning Repository, or Google Dataset Search.
Join the Community – Engage with forums, open-source projects, and hackathons to improve skills.
By following this roadmap, you’ll build a strong foundation and be ready to tackle more advanced ML topics.