What are the 3 main types of AI & ML learning and how to design a learning system?
What are the important points regarding Training vs Test Distribution?
What are the different function representations and search/optimization algorithms?
What are the different metrics used to control the quality of the predictions?
Part 2: Data Wrangling
Why is data pre-processing necessary in AI/ML?
What data pre-processing steps need to be taken before building a model? – Data cleaning, data integration and transformation, data reduction, discretization and concept hierarchy generation.
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