Machine Learning

01. What is Machine Learning?  

Machine Learning is a subset of artificial intelligence. It focuses mainly on the designing of systems, thereby allowing them to learn and make predictions based on some experience which is data in case of machines. 

• Artificial Intelligence: A technique which enables machines to mimic human behaviour 

• Machine Learning: Subset of AI technique which use statistical methods to enable machines to improve with experience. 

• Deep Learning: Subnet of ML which make the computation of multi-layer neural network feasible. 

Machine Learning Types

• Supervised

• Unsupervised 

• Reinforcement 

Supervised Learning

An examples of Supervised Learning 

• Linear Regression 

• Random Forest

• Support Vector Machines 

Use case of Supervised Learning 

• Speech recognition 

• Weather prediction 

• Bio metric detection 

• Banking sector, predict worthiness 

• Healthcare sector

• Retail sector, identify frequently buy together 

Unsupervised Learning: based on characteristic 

algorithm is left on it's own to discover unique chararistic on it's own

• Apriori Algorithm 

• K-Means Algorithm 

• Hierarchical Clustering 

An example of unsupervised learning.

• Banking sector: Segment customers by behavioural characteristices 

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15 min