Download Machine Learning

Artificial Intelligence is the branch of computer
science concerned with making computers behave
like humans. The term was coined in 1956 by John
McCarthy at the Massachusetts Institute of
Technology.
The event which led to the birth of AI ,Organised by Marvin Minsky, John
McCarthy and two senior scientists: Claude Shannon and Nathan
Rochester of IBM.
“Every aspect of learning or any other feature of intelligence can be so precisely
described that a machine can be made to simulate it"
A branch of artificial intelligence , concerned with the
construction and study of systems that can learn from data
Programs that can automatically improve their performance
through experience without explicit programming
Focuses on the development of computer programs that
can teach themselves to grow and change when exposed
to new data.
Learning = Improving with experience at some task
• Improve over task T
• With respect to performance measure P
• Based on experience E
• Classification : Predict class from observations.
• Clustering: Group observations into “meaningful” groups.
• Regression (prediction): Predict value from observations.
• Classify a document into a predefined category.
• Documents can be text, images
• Popular one is Naïve Bayes Classifier.
• Steps:
1. Train the program(Building a model) using a training set with a category for e.g.
sports, news,..
Classifier will compute probability for each word, the probability that it makes a
document belong to each of the considered categories.
2. Test with a test data set against this model.
• Clustering is the task of grouping a set of objects in such a way that the objects in
the same group ( called a cluster) are more similar to each other.
• Objects are not predefined.
• For e.g. these keywords.
“men’s shoe”
“women’s shoe”
“women’s t-shirt”
“men’s t-shirt”
Can be clustered into 2 categories “shoe” and “t-shirt” or “men” and “women”
• It is a measure of the relation between the mean value of one variable (e.g. output) and
corresponding values of other variables(e.g. time and cost)
• Regression analysis is a statistical process for estimating the relationships among
variables.
• Regression means to predict the output value using training data.