Artificial Intelligence and Machine Learning

 

Instructor

Pradipta Biswas, PhD (Cantab)

Intelligent Inclusive Interaction Design Lab

Assistant Professor

Indian Institute of Science

Email: pradipta AT iisc DOT ac DOT in

Prerequisite

·        Basic knowledge of Mathematics

·        Basic knowledge of probability and statistics

·        C++ and preferably C# or VB.Net programming skill

What you get

·        Introduction to different AI algorithms

·        Introduction to Machine Learning

·        Case Studies

·        Qualitative and Quantitative Data Analysis

 

·        Lecture 1: Introduction to Artificial Intelligence, Case Studies from Fashion Technology [Lecture notes] [Case Studies]

·        Lecture 2: Heuristic Search Algorithms, Complexity Analysis, State Space Modelling, Application on developing Intelligent User Interface [Lecture notes]

·        Lecture 3: Uncertainty Modelling, Conditional Probability, Bayes’ Rule, Certainty Factor, Expert System [Lecture notes] [Expert System Example]

·        Lecture 4: Bayesian Inferencing, Bayesian Network, Naïve Bayes Classifier [Lecture notes] [Case Study]

·       Lecture 5: Introduction to Machine Learning, Classification and Clustering, Backpropagation Neural Network, Cluster Validation Index, Case study on predicting pointing target [Lecture Notes] [Neural Network Example]

·        Lecture 6: Quantitative Data Analysis, Statistical Hypothesis Testing, Parametric and Non Parametric Tests, t-test, ANOVA, Chi-Square tests, APA Reporting Style [Lecture Notes]           [Sample dataset and analysis]

·        Lecture 7: Case studies on image processing and computer vision [Lecture I] [Lecture II]

·        Workshop on CLIPS Expert System, ML toolboxes and eye gaze tracking sensors

·        Lecture 8: Qualitative Data Analysis, Different Techniques to collect Qualitative Data, Introduction to Analysing Free Text Data  [Lecture Notes]

·        Lecture 9: Sequential Decision Process, MDP, Case Study on developing a cognitive model [Lecture Notes]

·        Lecture 10: Partial Order Planning [Lecture Notes]

 

References

Russell S and Norvig P., A Modern Approach to Artificial Intelligence

Field A., Statistics with SPSS