Why machine learning prevalent today? - Machine Learning Tutorial

Machine learning is a field that had grown out of the field of AI, or Artificial Intelligence. We want to build intelligent machine and it turns out that there are a few basic things that we could program a machine to do such as how to find the shortest path from A to B. But for the most part we just did not know how to write AI programs to do the more interesting things such as Web Search or Photo Tagging or Email Anit-Spam. There was a realization that the only way to do these things as to have a machine learn to do it by self. So, machine learning was developed as new capability for computer and today it touches many segments of industry and basic science.

Some other examples of machine learning

  • Database Mining
    One if the reasons machine learning has so pervaded is the growth of the web and growth of automation All this means that we have much larger data sets than ever before.

  • Examples
    1. Web Click Data
    Tons of companies are today collecting web click data also called clickstream data, and are trying to use machine learning algorithms to mine this data to understand user better and o serve the users better.

    2. Medical Records
    With the advent of automation, we now have electronic medical records. So if we can turn medical records into medical knowledge, then we can start to understand disease better.

    3. Computational Biology
    With automation again, biologist are collecting lots of data about gene sequences, DNA sequences, and so on, and machine learning algorithms are giving us a much better understanding of the human genome, and what it means to be human.

    4. Engineering
    And in engineering as well, in all fields of engineering, we have larger and larger and larger and larger data sets, that we're trying to understand using learning algorithms.

  • Application can't program by hand
    A second range of machinery applications is once that we cannot program by hand, so far, examples -

  • Autonomous Helicopter

  • Handwriting Recognition

  • Natural Language Processing (NPL)

  • Comupter Vision

These are the fields of AI pertaining to understanding language or understanding images. Most of NLP and Computer Vision today is applied machine learning.

  • Self customizing programs
    Learning algorithms are also widely used for self customizing programs. Examples
  • Every time you go to Amazon or Netflix and it recommends the products and movies to you, that's a learning algorithm. If you think about it they have million users; there is no way to write a million different program for your million users. The only way to have software give these customized recommendation is to become learn by itself to customize itself to your preferences.

Finally learning algorithms are being used today to understand human learning and to understand brain. We'll talk about how researchers are using this to make progress towards the big AI dream.


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