Page 164 - Ai Book - 10

Sample Cluster/group

z Dimensionality Reduction: A dataset contains a huge number of input features in various cases, which
makes the prediction more complex. In such cases, dimensionality reduction technique is used as it
is a way of converting the higher dimensions dataset into lesser dimensions dataset ensuring that it
provides similar information. This technique is widely used in machine learning for obtaining a better fit
predictive model while solving the classification and regression problems. A simple email classification
problem is an example of dimensionality reduction where we need to classify whether the email is
spam or not. This process can involve a large number of features such as generic title, content of the
e-mail, any template use in e-mail etc. To do this, we can use dimensionality reduction algorithms to
reduce the number of features in such types of problems.

u Reinforcement Learning: Reinforcement learning refers to the process of training the machine learning
models to make a sequence of decisions. In reinforcement learning, machines learn how to achieve a goal
in an uncertain, potentially complex environment.

The FBI uses machine learning to detect potential terrorist activity by tracking mobile messaging apps
and social media platform.

AI Activity
AI Activity
Machine Learning
AI for Oceans
AI for Oceans is an application that helps us to learn about artificial intelligence, machine learning,
training data, etc. while addressing the global issue, i.e. Water Pollution. To use the application,
follow the given steps:
Step 1: Go to the Web Browser and type the following URL in the address bar: https://code.org/
oceans.
Step 2: Click the Try Now button. The following screen appears.

38
38