MACHINE LEARNING

 The Era in which we are living right now is the "AGE OF DATA". Today , we have a massive amount of data that is constantly increasing every-day, Better computational power and more storage resources, However the real challenge is to make a sense of all the data. Therefore , companies are busy building intelligent systems using concepts and methodologies from computer science,  MACHINE LEARNING AND DATA MINING. " MACHINE LEARNING IS THE BUZZ WORD TODAY !" I involves applications and algorithms that provide sense to the data.



Machine Learning(ML) enables computer system to provide sense to data in much the same way as Human Beings do. It is a branch of ARTIFICIAL INTELLIGENCE that extracts patterns  from raw data by using a well defined algorithms. (ML) allows the computers to learn from experience without human intervention.
 

NEED FOR MACHINE LEARNING:

We all know that human beings are the most intelligent species on the planet, Human can think, evaluate and solve complex problems. Therefore Human now wants to imbibe this intelligence in machines so that even they can think, analyze and act to deduce solution to  otherwise complex problems.

  • In continuation to this, ML aims at enabling the machines make decisions , based on data, with efficiency and scale particularly to automate the data-driven decision making process.
  1. Lack of availability of human expertise, or in situations where it is not safe or partially feasible for humans to work .
  2. Dynamic scenarios where conditions keep changing fast and human are quit slow to response
  3. Difficulty faced by humans to provide 100% accurate results especially for computational task.
CHALLANGES IN MACHINE LEARNING: 

 All is not good with respect to  ML. There are multiple issues with respect to cyber security. Apart from this , other significant factor can be given as :

  • Availability of good-quality data for application of ML algorithms.
  • Time consuming and exhaustive set of tasks involved in data acquisition , feature extraction and retrieval.
  • Lack of expertise as ML is still in its infancy stage.
  • Issue of overfitting and underfitting the model.
APPLICATION OF MACHINE LEARNING: 

ML is growing area. Its application to solve real world problems is constantly rising, These days ML is being extensively used for -

> Emotion Analysis

>Sentiment Analysis

>Error Detection and Prevention

>Weather Forecasting and Prediction.

>Stock Market Analysis and Prediction

>Speech Synthesis

>Speech Recognition  And much more....!!




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