Machine Learning for Interviews & Research and DL basics

Interested in Machine Learning, and Deep Learning and preparing for your interviews or research? Then, this course is for you!The course is designed to provide the fundamentals of machine learning and deep learning. It is targeted toward newbies, scholars, students preparing for interviews, or anyone seeking to hone the data science skills necessary. In this course, we will cover the basics of machine learning, and deep learning and cover a few case studies.This short course provides a broad introduction to machine learning, and deep learning. We will present a suite of tools for exploratory data analysis and machine learning modeling. We will get started with python and machine learning and provide case studies using keras and sklearn.### MACHINE LEARNING ###1.) Advanced Statistics and Machine LearningCovarianceEigen Value DecompositionPrincipal Component AnalysisCentral Limit TheoremGaussian DistributionTypes of Machine LearningParametric ModelsNon-parametric Models2.) Training Machine Learning ModelsSupervised Machine LearningRegressionClassificationLinear RegressionGradient DescentNormal EquationsLocally Weighted Linear RegressionRidge RegressionLasso RegressionOther classifier models in sklearnLogistic RegressionMapping non-linear functions using linear techniquesOverfitting and RegularizationSupport Vector MachinesDecision Trees3.) Artificial Neural NetworksForward PropagationBackward PropagationActivation functions