Machine Learning Algorithms | Machine Learning Tutorial | Data Science Tutorial | Edureka

1. Edureka’s Data Science Certification Training www.edureka.co/data-science

2. Agenda for Today’s Session What is an Algorithm? What is Machine Learning? How is a problem solved using Machine Learning? Types of Machine Learning Machine LearningAlgorithms Demo Edureka’s Data Science Certification Training www.edureka.co/data-science

3. What is an Algorithm? Edureka’s Data Science Certification Training www.edureka.co/data-science

4. What is an Algorithm? To tell a computer what it has to do, you need a program. Edureka’s Data Science Certification Training www.edureka.co/data-science

5. What is an Algorithm? To tell a computer what it has to do, you need a program. A program is nothing but logic in some language’s syntax Edureka’s Data Science Certification Training www.edureka.co/data-science

6. What is an Algorithm? To tell a computer what it has to do, you need a program. logic This logic is what an Algorithm is Edureka’s Data Science Certification Training www.edureka.co/data-science

7. What is an Algorithm? A process or set of rules to be followed in calculations or other problem-solving operations, especially by a computer Edureka’s Data Science Certification Training www.edureka.co/data-science

8. Algorithm - Example Start Initialize X = 0 Increment X by 1 This is a simple algorithm to print numbers from 1 to 20. Print X YES X< 20 NO END Edureka’s Data Science Certification Training www.edureka.co/data-science

9. What is Machine Learning? Edureka’s Data Science Certification Training www.edureka.co/data-science

10. What is Machine Learning? Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. Machine learning focuses on the development of computer programs that can change when exposed to new data. Edureka’s Data Science Certification Training www.edureka.co/data-science

11. Machine Learning Types Edureka’s Data Science Certification Training www.edureka.co/data-science

12. Categories of Algorithms Types of Learning Supervised Learning Reinforcement Learning Unsupervised Learning Edureka’s Data Science Certification Training www.edureka.co/data-science

13. Supervised Learning Supervised learning is a type of machine learning algorithm that uses a known dataset (called the training dataset) to make predictions. The training dataset includes input data and response values. From it, the supervised learning algorithm seeks to build a model that can make predictions of the response values for a new dataset. Supervised Learning Let’s take an example here. Say you are a teacher, and your way of teaching is, To teach by example, i.e for every problem in their life you are providing solutions to them, this type of learning is called supervised learning. Unsupervised Learning Teaching by Example Reinforcement Learning Let’s take the same example forward: Edureka’s Data Science Certification Training www.edureka.co/data-science

14. Unsupervised Learning Unsupervised learning is a type of machine learning algorithm used to draw inferences from datasets consisting of input data without labeled responses. Supervised Learning When your kids are taking decisions out of their own understanding, this type of learning would be Unsupervised Learning. Unsupervised Learning Self Learning Reinforcement Learning Edureka’s Data Science Certification Training www.edureka.co/data-science

15. Reinforcement Learning Reinforcement learning is an area of machine learning inspired by behaviorist psychology, concerned with how software agents ought to take actions in an environment so as to maximize some notion of cumulative reward. Supervised Learning If a new situation comes up, the kid will take actions on his own i.e from his past experiences, but as a parent towards the end of an action you can tell him whether he did good or not. Unsupervised Learning Good or Bad? Reinforcement Learning Edureka’s Data Science Certification Training www.edureka.co/data-science

16. How a problem is solved using Machine Learning? Edureka’s Data Science Certification Training www.edureka.co/data-science

17. How a problem is solved using Machine Learning? We take a top down approach to answer the same: These are the 5 questions which can be answered in data science. Classification Algorithm Is this A or B? Q1. Anomaly Detection Algorithm Is this weird? Q2. Regression Algorithms How much or how many? Q3. How is this organized? Clustering Algorithms Q4. Reinforcement Learning What should I do next? Q5. These algorithms are fitted into three types of categories, which are the following: Edureka’s Data Science Certification Training www.edureka.co/data-science

18. Machine Learning Algorithms Edureka’s Data Science Certification Training www.edureka.co/data-science

19. Classification Algorithms Classification Algorithms are used to classify a record. It is used for questions which can have only a limited number of answers. For Example: Yes or No Is it cold? Yes, No or Maybe Yes, No or Maybe Will you go to work today? When you have only two choices, its called 2 class Classification, if you have more than 2 choices its called Multi Class Classification Edureka’s Data Science Certification Training www.edureka.co/data-science

20. Anomaly Detection Algorithms It analyzes a certain pattern and alerts you whenever there is change in the pattern. For Example: Anomaly Did you know? Oh! In real life, your credit card company uses these anomaly detection algorithms, and flag any transaction, which is not usual as per your transaction history Edureka’s Data Science Certification Training www.edureka.co/data-science

21. Regression Algorithms Regression Algorithms are used to calculate numeric values. For example: What will the temperature be tomorrow? How much discount can you give on a particular item? Edureka’s Data Science Certification Training www.edureka.co/data-science

22. Clustering Algorithms It helps you understand the structure of a dataset. These algorithms separates the data into groups or clusters, to ease out the interpretation of the data. Group A Group C Group B By understanding, how data is organized, you can better predict the behavior of a particular event Edureka’s Data Science Certification Training www.edureka.co/data-science

23. Reinforcement Algorithms These algorithms were designed as to how brains of humans or rats respond to punishments and rewards, they learn from outcomes, and decide on next action. They are good for systems which have to make lot of small decisions without human guidance. For example: A system which plays chess A temperature control system, when it has to decide whether temperature should be increased or decreased Edureka’s Data Science Certification Training www.edureka.co/data-science

24. Demo Edureka’s Data Science Certification Training www.edureka.co/data-science

25. Dataset A sample dataset to be used is divided like this: Training Dataset Testing Dataset Edureka’s Data Science Certification Training www.edureka.co/data-science

26. Thank You … Questions/Queries/Feedback Edureka’s Data Science Certification Training www.edureka.co/data-science