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Machine Learning – The Intelligent Machine
In simple words, we can say that machine learning is the competency of the software to perform a single or series of tasks intelligently without being programmed for those activities. This is part of Artificial Intelligence. Normally, the software behaves the way the programmer programmed it; while machine learning is going one step further by making the software capable of accomplishing intended tasks by using statistical analysis and predictive analytics techniques.
You may have noticed that whenever we like or comment a friend’s pictures or videos on a social media site, the related images and videos are posted earlier and keeps on displaying. Same with the ‘people you may know’ suggestions, the system suggests us other user’s profiles to add as a friend who is somehow related to our existing friend’s list. Wondering! How does the system know that? That is called Machine learning. The software uses the statistical analysis to identify the pattern as a user you are performing, and using the predictive analytics it populates the related news feed on your social media site.
What is the Need of Machine Learning?
Generally, the software works the way it is programmed, there are hundreds and thousands of complex codes written to execute the desired works. The programmer writes the codes and the software performs the planned task wonderfully provided there is no defect inside. So, when everything is going well by programming the software, then what is the need of machine learning? Why is it necessary to make the software recognize the vast data and determine the next course of actionable task?
Let’s discuss one simple example which we normally perform every day as part our online activities, that is searching something on the Google or any other Search Engines. So, whenever we search something, the search engine displays the links of related web pages within seconds. So, can that be possible just by programming the search results to display the related web links based on the words or sentences we typed in on the search bar?
There are millions of people searching the web at a time, and there are many new websites launching every minute. So, can Google or any other search engine providers able to decide which related search contents will be shown on the search results page just by doing the programming at runtime? That is completely impossible. So, how it works? Let’s find out how it is possible using the machine learning techniques.
How Machine Learning Works?
Machine Learning is a technique which works intelligently by using some complex algorithms and set of predefined rules. It uses the past data to read the patterns and then based on the analysis it generates the relevant data or performs the intended task abiding the defined rules and algorithms.
As we discussed earlier in the search example, whenever we typed in something on the search bar, the search engines uses this machine learning technique to display the related contents. It intelligently reads the vast data on the web, indexes, ranking, and based on the defined rules and algorithm it displays the search results.
Let’s discuss the basic steps involved in machine learning techniques.
- The first step is to gathering the past data from the various sources such as excel files, text files or any other provider. The quality of related data is the foundation of learning for the software, the more relevant the data, the better learning for the software
- The next step is data preparation. The programmer spends time on preparing the quality data and fixing the data issues. The missing data should be rectified to improve the data quality.
- Develop the data model with appropriate algorithms. The models are developed and tested with relevant algorithms which enable the software to read the correct data sets intelligently in the real world
- Next step is to testing the model’s accuracy using the data sets used while developing the models and also the data sets which were not used while developing the models. It shows the model’s performance and accuracy with the optimum level of precisions.
- Finally, check and improve the performance by using various data sets which were not used earlier. That shows the software’s capabilities to read new data sets based on the rules defined in the programmed algorithms.
Few More Examples of Machine Learning
As we discussed earlier, how the Google and other search engines providers use machine learning techniques to populate the relevant data. Let’s see some of more examples where machine learning techniques have been used to populate the related data.
Diagnosis of Deadly Diseases
The machine learning technique is being used in the field of healthcare domain. The software helps to detect the deadly diseases such as cancers by reading the past data of the patients and matching that with the symptoms defined in the algorithms.
Face Reorganization and Tagging Features
You may have noticed that, while uploading the images into your social media accounts, the software suggests the name of your friends present in the images for tagging. It asks you to whether you want to tag the person whose face is in the uploaded images.
This is possible by using the machine learning techniques. It recognizes the faces of the people present in the images by using the past data of those users and suggests you the accurate names.
Detection of Spam Emails
This is another example which we experienced in our email account. There are emails which directly go to the spam folders instead of inbox, why? That is again the machine learning techniques being used by the software.
The software model identifies the email messages based on the nature of the content it carries and decides whether it is a spam or a genuine email to be allowed to the inbox. The software reads the past data feeds and the set of rules and algorithms to identify the nature of the emails.
Displaying the Related Advertisements
While reading an online article or seeing images or videos, you may have noticed that the related advertisements from various advertisers to buy or see a product keep on coming on the side bars and elsewhere on the web pages.
That is again an example of machine learning. The software recognizes the data used in the articles and shows the related products which the users may be interested in buying or seeing.
There are many such examples from the banking, e-commerce, Robots to the astronomy and the medical science fields where machine learning techniques are being used. You can found the usage of machine learning techniques in most of the applications where the vast amount of data being used.
Finally, the machine learning technique is the need of today’s business where we are dealing with huge volume of data that keeps on adding every second. That cannot be managed just by writing piles of complex codes.
- What is Machine Learning?
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- Learning Model Building in Scikit-learn: A Python Machine Learning Library
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- How is machine learning used in regular life?