Machine Learning and its Applications
Machine learning is a data science technique used to extract patterns from data, allowing computers to identify related data, and forecast future outcomes, behaviors, and trends.
Before we start breaking the above statement down, let us first understand how machine learning is different from traditional programming.
In Traditional Programming, we provide hard-coded rules and data to the computer to get output or results or answers. In other words, the set of rules by which the computer has to operate on the data are provided beforehand.
Whereas in Machine Learning, we provide the data and results or answers to the computer and it returns the rules.
It is very difficult to write high performing traditional programs for applications such as fraud detection, image classification, object detection, speech recognition, etc. And we are not sure what the exact rules should be. Machine Learning comes into play there. It allows computers to learn automatically based on observation or data.
Now coming back to our first statement.
Let us take an example of Flight Services Prediction, imagine we had some previous data on everyday flight services. This data comprised details such as flight name, destination, departure time, number of people on board, weather conditions, etc.
Now we wanted to predict whether or not that particular flight is delayed or not. How do we do that? We don’t know any exact rules or algorithms to solve the problem using traditional programming.
We can use machine learning to extract patterns from the data available, understand them, and predict the outcome. We feed the data of everyday services to the computer, let the algorithm explore the relationship to come up with rules.
Maybe the weather conditions have an impact on flight delays. We let the computer figure out from the data on previous trends.
This was one of the many applications of Machine Learning.
Let us explore some more.
APPLICATIONS OF MACHINE LEARNING
- IMAGE PROCESSING
- PRODUCT RECOMMENDATION SYSTEMS
- MEDICAL DIAGNOSIS
- ONLINE FRAUD DETECTION
- SPEECH RECOGNITION
Image Processing:-
Image processing means processing the digital image to either enhance the image or extract useful information from it. Basically, the input is an image and the output is an image or its features.
Product Recommendation Systems:-
Recommendation Systems have created a revolution in the business industry. Using machine learning, one can build systems that recommend products that a specific user would like to purchase or engage with. You all must have noticed Amazon suggests you products that you've recently viewed or searched. Now you know that's how it's done.
Medical Diagnosis:-
In the medical field, ML is particularly useful in perfect diagnoses, recommending medicines, and identifying high-risk patients. Hence reducing physician burnout. For example, Google has trained a deep learning model to detect breast cancer and Stanford researchers have used deep learning models to diagnose skin cancer.
Online Fraud Detection:-
Due to the increase in online transactions through different payment modes, there is also an increase in the number of frauds. ML can be used to create a fraud detection algorithm to solve this real-world problem.
Speech Recognition:-
Speech recognition is the ability of a machine to recognize speech within audio and converting it into a machine-readable or text format. It is particularly useful for the elderly and visually impaired to quickly and easily interact with products or services. An example of this could be Amazon Alexa.
