MOOCS

Machine Learning From Applied Ai Course

This course provides a broad introduction to machine learning,deep learning, and statistical pattern recognition.
Topics include:
(i) Supervised learning (parametric/non-parametric algorithms,KNN,Naive Bayes,Linear Regression,Logistic Regression, support vector machines, kernels,Decsions tree,Ensembe Modeling, Neural networks,CNN,RNN,LSTM).
(ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning).
(iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI).
The course will also draw from numerous case studies and applications, so that you'll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.