Supervised learning

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Supervised Learning
Swipe
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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.
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Types of Machine Learning
Unsupervised
Supervised
Reinforcement
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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 learning more specifically,
  clustering include Customer segmentation, or
  understanding different customer groups.
  Unsupervised learning is commonly used for
  finding meaningful patterns and groupings
  inherent in a given or collected date set.
• Reinforcement is a type of Machine Learning
  algorithm

which allows automatically
software agents and machines to
determine the ideal behavior within a
specific context, to maximize its performance.
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Supervised Learning Process Flow
. Training Dataset
Training and Validation
. .
. .
Learning . Model
Machine Statistical
Historical data
Random Sampling
. Test Dataset
.
Prediction, Validation
Model validation outcome
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Supervised Learning Process Flow
Prediction
.
.
Prediction
Prediction outcome
New Data
.
Statistical model
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Supervised Process 2 Steps
Learning Training Testing
Training data
Learning Algorithm
Test data
Model
Accuracy
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Topics for next Post
Support Vector Machines Linear regression
Logistic regression Stay Tuned with