Machine Learning, its Introduction and types

Introduction about Machine Learning

1. Introduction to Machine Learning

2. Agenda What is Machine Learning ? Why Machine Learning ? ML Life cycle Definition of ML Types of ML Supervised Learning Unsupervised Learning Reinforcement Learning Applications of ML Q&A

3. What is Machine Learning ? Machine Learning is a science of Making computers Learn and act like humans by feeding data and information without being explicitly programmed. Is machine learning only for making computers/bots behave like humans ?

4. Machine Learning Life Cycle

5. Defination of ML According to Arthur Samuel (in 1959) , ML is field of study that gives computers the ability to learn without being explicitly programmed. & According to Tom Mitchel (in 1998) ,A computer program is said to learn from experience E with some class of task T and some performance measure P ,if its performance P on task T , as measured by P, improves with experience E.

6. Types Of Machine Learning

7. Supervised Learning Supervised learning is where you have input varibles (x) and output variable (y) and you use an algoritham to learn the mapping function from the input to output. Here data is provided with label which is most important thing for supervised learning.

8. Supervised Learning

9. As name itself suggest that , its opposite to that of supervised learning because here data is provided without label and random. So , here clustring is used which is the best algorithm For unsupervised learning , it finds the hidden structure of data and also hidden data . Unsupervised learning is mostly used for Data mining as it finds the hidden data and their structure. Unsupervised Learning

10. Unsupervised Learning

11. Reinforcement Learning Reinforcement learning is a type of machine learning where an agent learns to behave in an environment By performing actions and observing the outcomes(results). It is simply means that here the agent requires the feedback of environment and environment can be anything it may be a human , thing or another computer .

12. Reinforcement Learning

13. Applications of Machine Learning Virtual asistant Google map Marketing Face , voice,pattern Recogonition Predicting deases Computer vision Computer network Brain machine interface Games (modern)

14. Thank You