If you have Data ask me. Everything else ask God.
This course will provide an overview of basic ideas in statistical machine learning. The course should be useful to applied scientists from any discipline wo would like to use statistical machine learning in their research and data analysis. No previous knowledge neither any rigorous training in mathematical statistics is required.Topics:
The topics to be covered include: Supervised learning, classification, algorithms and unsupervised learning. The course begins with detailed discussion of supervised learning. It will discuss the sub-topics of regression where the usual topics of multicollinearity, variable selection, regularisation, LASSO prior, Ridge prior, Elastic Net prior will be illustrated with many examples. This will be followed by the discussion of non-linear regression where we will also consider the topics of Gaussian Process Prior Regression.
The topic of Classification will be discussed with special emphasis on the naive Bayes classifier, Discriminant Analysis, logistic regression, Decision Tree, Support Vector Machine, Random Forest, Neural Network and Deep Learning.
Next, we will discuss various popular algorithms such as the Gradient Descent, Stochastic Gradient Descent and Back Propagation. Unsupervised learning is the last major topic to be discussed in this course. Here we will introduce the K-means clustering and principal component analysis.
The courses will have a large practical hands on traning component for which participants are required to bring their own laptop. Methods will be illustrated using several practical examples from banking, system bilogy, environmental sciences etc.
R-code and data sets will also be provided at the beginning of the courses.
Three to five days format: This format is primarily aimed at applied scientists and professionals who wish to use the statistical machine learning ideas in their data analysis and modeling problems. The courses will be suitable for applied scientists and statisticians from government departments, practitioners from industry, and research students at all levels. Academic researchers and scientists from other disciplines can also attend. People from industry, who aspires to grow in the technical ladder, will find it useful.
One day format:
This format is primarily aimed at applied scientists and professionals who wish to become familiar with the statistical machine learning ideas in their work. The courses will be suitable for applied scientists and statisticians from government departments, practitioners from industry, who aspires to be on the admin side. People from industry, who wants to grow in management ladder, will find it useful.
In one day format we donot do any handson. Main focus of this format is to understand the big picture.
Recently, I delivered the 3-day format of the course at the University of Southampton, UK, during June 13-15, 2018