Before we go and start understanding various machine learning algorithms, let us discuss the end-to-end framework of data science deployment. We will talk about many interesting concepts and walk you through who should own which part and what should be the expected output of each part.

An objective function in the context of machine learning is a mathematical function that quantifies how well the algorithm is performing at a particular task.

Now before we jump onto the next section, let us check our understanding of Module 1. Take the Module 1 Quiz by clicking on the button on the right side.You will see your scores and right answers upon completion of the quiz.

We have reached a point in our journey where we can start playing with some key applications of AI to learn why suddenly AI has gained an inflection point. We discussed some key applications of AI in Lesson 1.

we discussed how Machines learn i.e. Supervised, Unsupervised, and Reinforcement Learning. More and more companies are building products leveraging these learning techniques. But companies are not only leveraging data to teach machines but also leveraging data to learn more about the past, and the future, and make business recommendations. This is what is called Advanced Analytics.

If we say that AI is about enabling a machine to think (and act) like a human, then a question that needs to be answered is how do we determine that machine has actually started thinking like a human. The answer to this question was first answered with the introduction of the concept Turing Test.