basics of machine learning
Post on 18-Jul-2015
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ObjectiveEntice you to want to go learn more about machine learning.
Data is huge. People are expensive. Computation is cheap.
Use applied statistics to let the computers program themselves.
Types
Types
Supervised "I have a set of examples with the right answers, I want to learn a pattern and use it on examples where I don't have the answers."
Types
Unsupervised "I have data with no answers, but I want to find a pattern that might lead me to an answer."
TypesReinforcement "I want to start with what I know now, and be able to learn new things as they come along."
Types
Supervised "I have a set of examples with the right answers, I want to learn a pattern and use it on examples where I don't have the answers."
Unsupervised "I have data with no answers, but I want to find a pattern that might lead me to an answer."
Reinforcement "I want to start with what I know now, and be able to learn new things as they come along."
Types
Supervised "I have a set of examples with the right answers, I want to learn a pattern and use it on examples where I don't have the answers."
Unsupervised "I have data with no answers, but I want to find a pattern that might lead me to an answer."
Reinforcement "I want to start with what I know now, and be able to learn new things as they come along."
Regression vs Classification
Supervised Learning
RegressionUse continuous data to make a model that predicts where new data will fit.
ClassificationLabel data into "buckets", and make predictions on which bucket a new data point will fall into.
Where to learn more
Books
Podcasts
Interactive
Where to learn more
Books
Podcasts
Interactive
Where to learn more
Books
Podcasts
Interactive
Where to learn more
Books
Podcasts
Interactive
Where to learn more
frankdevans
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