What is the difference between machine learning and Learning from Data?

[pouramini]

In the book I can't see the difference between machine learning and learning from data, are they equivalent? Is LFD a sub-filed of ML?

The ML definition I found is "A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E"

It doesn't restrict the experience E? Does LFD refers to this definition or it has a narrower definition?

[yaser]

They are the same. Machine Learning is a legacy term (as a counterpart to human learning) that has been the prevalent name of the field. Learning From Data is a descriptive name of what the field is about.

[pouramini]

You mean all learning problems in ML are learning from data? Isn't possible to learn from something else? for example in learning to play a checker game or learning to drive a robotic automobile autonomously, what is data?

Also the definition I found emphasizes on designing a good learning experience and performance measure, but in your definition it seems they are same for any problem. the measure is the accuracy of algorithm on unseen data and the experience is training data set. Are these right?

[yaser]

There are variations, but the bulk of machine learning as it has been practiced is based on data. Out-of-sample performance has been the standard measure of performance in supervised learning.

[pdsubraa]

I go with Mr. Yaser and book references. Both are similar to some point.

[Ttacycurammeng]

Originally Posted by pouramini

In the book I can't see the difference between machine learning and learning from data, are they equivalent? Is LFD a sub-filed of ML?

The ML definition I found is "A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E"

It doesn't restrict the experience E? Does LFD refers to this definition or it has a narrower definition?

Machine learning is an application of artificial intelligence that automates analytical model building by using algorithms that iteratively learn from data without being explicitly programmed where to look.

Machine Learning Pre-requisite knowledge

Vectors
• Matrix proper+es, e.g. determinant, rank, inverse
• Vector Space proper+es, e.g. orthonormal basis
• Eigenvectors and Eigenvalues
• Matrix Calculus, e.g. deriva?ves in matrix form
• Op+misa+on basics, e.g. Lagrange mul?pliers

Learing from data

Learing from data is a key technology in Big Data, and in many financial, medical, commercial, and scientific applications. It enables computational systems to adaptively improve their performance with experience accumulated from the observed data.

Learning from Data ….. Prerequisites

MATHEMATICS This is a mathema+cal subject. You must be comfortable with probabili+es and algebra. PROGRAMMING You must be able to program, and pick up a new language rela.vely easily. We provide support for Matlab.

Learning from Data ….. Why NOT to do this!
If you don’t like maths. 61011 is reasonably challenging. 61021 is HARD. Another valid name for machine learning is “Computa.onal Sta.s.cs”. 2. If you are not a confident programmer. This is an MSc in computer science. You HAVE to be able to code well. You are highly likely to fail this unit if you cannot. People did last year. 3. If you have the “I want to use machine learning to do X” syndrome This is a real technical subject. It’s not magic.

( BTW… You will learn nothing about “Big Data”, or how to deal with it)

[pdsubraa]

Thumbs up! Thanks!