Simply speaking, Machine Learning is a set of artifical intelligence techniques which are used to solve one of the following problems based on the examples in hand:
Machine learning is a key aspect of data science. It allows data scientist to apply existing data sets to one of the machine learning algorithm and predict based on that. In other words, a person wanting to become a data scientist must learn machine learning algorithms to be able to predict/recommend.
Following are key steps in machine learning:
Above steps of machine learning could be represented using following, from API perspective. Thus, whether using R, or pyhton APIs, following is how the API structure would look like:
# Model created based on a given data set
model = createModelAPI(existingDataSet)
# Model is fed with new dataset, newDataSet which gives predicted output, predictedOutput
predictedOutput = createPredictionAPI( model, newDataSet )
Lets take an example of linear regression using R programming console. Look at the code below:
# Linear regression model
model = lm( price ~ carat, data=diamonds )
price = predict( model, newData )
# Multiple linear regression model
model = lm( price ~ carat + cut + color, data=diamonds )
price = predict( model, newData )
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