Statistics heart & soul of Machine Learning: Raju Narayana Swamy

Hyderabad: Statistics is the heart and soul of machine learning, opined Kerala’s Anti-Corruption crusader Dr Raju Narayana Swamy, IAS. He was addressing a group of central service officers at the Administrative Staff College of India, Hyderabad. Statistics for machine learning is the study of collecting, analysing and interpreting data to help build better machine learning models, opined Dr Swamy. It provides the mathematical foundation to understand data patterns, make predictions and evaluate model performance. It also helps in understanding data distribution variability and selecting the most useful features. It can be used to validate model results and make decisions under uncertainty using hypothesis tests, confidence intervals and Bayesian methods. Addressing the questions as to why one should learn statistics for machine learning, Swamy said.

Swamy opined that it can help in four ways: understanding the data before training models, choosing the right algorithms for specific problems, evaluating model accuracy and performance, and handling uncertainty and variability in real-world data.

Underlining that statistics is the key component of machine learning, Swamy also outlined its broad applicability in various fields.

These include Feature Engineering, viz. selecting and transforming useful variables, Image Processing, viz. analysing patterns, shapes and textures, Anomaly Detection, viz. spotting fraud or equipment failures, Environmental Studies, viz. modelling land cover, climate and pollution, and Quality Control, viz. identifying defects in manufacturing.

Narrating that there are two commonly used types of statistics - Descriptive and inferential- Swamy opined that the latter is more useful when it comes to making predictions or inferences about a population based on a sample of data. Dr Subodh Kandamuthan, Dean, ASCI, presided over the function, which was held at the Dr Kakarla Subba Rao Centre for Health Care Management, Hyderabad.