Question

Question:

Discuss roles of Artificial Intelligence and Machine Learning in Big Data Analytics.

Distinguish between Supervised and Unsupervised learning.

Discussion Requirements:

Define the concept of Artificial Intelligence.

Define the concept of Machine Learning.

Explain the notions of Supervised and Unsupervised Machine Learning.

Describe the roles of Artificial Intelligence & Machine Learning in Big Data Analytics.

Answer 1

Roles of Artificial Intelligence and Machine Learning in Big Data Analytics :

• Artificial Intelligence is the field of computer science where intelligence are created in machines artificially. Thus the machine can work and react like a human being.
• Machine Learning is a core part or it is an application of artificial intelligence, where the machines are capable of automatically learn and improve from experience . We not need to program them for everything , they can learn from experiences.
• Big data is a large collection of data. In this field useful information are derived from the big data set. Big data are collections of data from sources like social media.
• Machine learning produce patterns from the data.
• It was very difficult for human beings to convert this huge data into useful information, because it contains many steps to perform on a large collection. Some steps are sorting, filtering etc.. .
• Artificial intelligence and machine learning helped a lot in the field of data analytics.
• They made processing of data easy.
• Human beings will be tired while working on even a small amount of data, but any AI and Machine Learning enabled machine can work for a large amount of time without any problem until any hardware or software issue occurs.
• Also the machine can learn from the data on which they are analyzing, this make them more powerful. It will increase the power of machine.
• They increased the speed of analyzing data.
• While they learn from data , they get more accuracy in the prediction.

Distinguish between Supervised and Unsupervised learning :

• They are the machine learning tasks.
• Supervised learning is a process by which a machine start to learn from a supervisor , means the machine is taught by a teacher.
• Unsupervised learning is a process where the machine is not trained by a supervisor.In this , machine group data based on patterns .
• In supervised learning input variables and output variables will be given.
• In Unsupervised learning only input data is given.
• Supervised learning has an aim of predicting what the output is.
• Unsupervised learning has the main aim to learn about the data on which it is processing.
• Example of supervised learning is Regression, Classification etc ..
• Example of unsupervised learning is Clustering , Association etc..