Headstart-Ml

As the world moves from compute-intensive system architectures to data-intensive system architectures, new technology roles like Product Analysts, Data Analysts, Data Engineers, ML Engineers, and Data Scientist have come up. So, statistics & probability become important concepts and hence, candidates interviewing for these new roles are generally asked questions to test these concepts. Even if you are not in these roles, and in the core Software Engineering domain instead, still statistics, probability, and SQL remain the core concepts for beginning to understand any dataset and derive any meaning or predictions out of it, or write any computer logic around it. ...

How is ML different from Traditional Programming? Traditional Programming involves the manual or scaffolded (i.e. already written previously and hence cloned/repeated) logical process of writing a way to convert a certain input into desired output according to certain predefined constraints. So in short: Traditional Programming: Input + Program (by coder) = Output Machine Learning (ML) and its related fields, in contrast, automate this manual process of coming up with the logical program by seeing a big set of correct inputs and their corresponding correct outputs, and “learning” this mapping of input to output called as model. ...