Supervised Learning

1. Supervised Learning Swipe

2. Machine Learning Machine learning is a branch of computer science that focuses on the research and development of algorithms that can learn from and predict data. Rather of following purely static programme instructions, such algorithms construct a model from sample inputs in order to generate data-driven predictions or choices.

3. Types of Machine Learning Unsupervised Supervised Reinforcement

4. Types of Machine Learning Supervised Learning is learning a function that maps an input to an output based on data input-output pairs. It infers a function from labeled training data consisting of a set of training data Unsupervised include: different customer groups. Unsupervised learning is commonly used for finding meaningful patterns and groupings inherent in a given or collected date set. learning more specifically, or clustering understanding Customer segmentation, Reinforcement is a type of Machine Learning algorithm which allows software agents automatically determine the ideal behavior within a specific context, to maximize its performance. and machines to

5. Supervised Learning Process Flow Training and Validation . . . Training Dataset . . Machine Learning. Prediction, Validation Statistical Model Historical data Random Sampling . Test Dataset . Model validation outcome

6. Supervised Learning Process Flow Prediction . . Prediction New Data Prediction outcome . Statistical model

7. Supervised Process 2 Steps Learning Training Testing Training data Learning Algorithm Test data Model Accuracy

8. Topics for next Post Support Vector Machines Linear regression Logistic regression Stay Tuned with