This course covers all the steps that one should take while solving a business problem through linear regression. This course will give you an in-depth understanding of machine learning and predictive modeling techniques using R. RStudio is an integrated development environment for R, a programming language for statistical computing and graphics. It is available in two formats: RStudio Desktop is a regular desktop application while RStudio Server runs on a remote server and allows accessing RStudio using a web browser.
R and Python are the most popular languages used for machine learning. Both open-source languages provide a huge repertoire of statistical and predictive tools. However, they take very different approaches to data analytics.
Artificial Neural Networks (ANN) are now a staple within the sub-field of Machine Learning called Deep Learning. Deep learning algorithms can be vastly superior to traditional regression and classification methods (e.g. linear and logistic regression) because of the ability to model interactions between features that would otherwise go undetected. The challenge becomes explainability, which is often needed to support the business case. The good news is we get the best of both worlds with Keras and lime.
This course has some pre-requisite to ensure that the candidates who enroll for it are well prepared to understand the course material. The pre-requisite is not too long and is also possible that a student can take a bridge course if pre-requites are not met.
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