Module 1 - What is AI? - Machine Learning
Within Unsupervised Learning type of ML, there exists:
Clustering and Dimensionality Reduction
Main Types of Machine Learning:
Unsupervised Learning, Supervised Learning, Reinforcement Learning
Clustering:
grouping subsets of data in a dataset based off a similar attributes
Classifying Images:
provide machine with set of images of cats / dogs and use that model to identify other cats & dogs in other images
Machine Learning is one way to achieve ___
AI, hence the subset relationship
Within Supervised Learning type of ML, there exists:
Regression and Classification
Machine Learning Def'n:
Subset of AI technique which uses statistical methods to enable machines to improve with experience -- note that AI only Mimics the behaviour, whereas ML Improves with experience
Linear Regression model types:
Underfit - under-represents the trend of the data Optimal - optimally represents the trends of the data Overfit - over-represents the trend of the data
Traditional Programming VS ML
Traditional Programming: Hardcode Rules & Decisions into the program using conditional structures ML: Provide dataset & desired outcomes, and ML creates a model to process other data
Machine Learning Tom Mitchell Def'n:
A computer program is said to learn from experience E w.r.t. some class of tasks T and performance measure P if its performance at tasks T, as measured by P, improves with experience E
Machine Learning AI4ALL Def'n:
Subset of AI, consists of techniques that enable computers to LEARN from the data and deliver AI applications
ML Ex: SPAM Filters
Task: Classify emails as spam or not as spam Experience: Analyzing emails & watching us label spam Performance: Percentage of emails correctly classified