Baby steps for Machine learning

1. You can’t be a master without basics. Also you need to have the core skills in those domains.
   • To use machine learning first know how to program. The Google Class for Python
   • Learn and Understand statistics, especially Bayesian probability, which is essential for many machine learning algorithms. Blog for free books on data science / statistics.
   • Also learn Scipy, numpy, pandas from youtube
   
   
2. After basics, it’s time to take some free courses from best universities
   • Stanford’s Machine Learning Course, this is the famous course by Andrew Ng
   • Harvard’s Data Science Course, this is End-to-end data science course. Get practice with the entire data science workflow from data collection to analysis
   • Read An Introduction to Statistical Learning and Elements of Statistical Learning
   
   
3. Practice the entire machine learning workflow: Data collection, cleaning, and preprocessing. Model building, tuning, and evaluation using real data sets. Pick 5-10 datasets from the UCI Machine Learning Repository. For example, you can pick 3 datasets each for regression, classification, and clustering.
4. Now go and participate in machine learning competitions.