Faculty of Science and Information Technology > Machine Learning/ Deep Learning

What Is Machine Learning? Why Machine Learning Matters ?

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motiur.swe:
A data analytics technique that teaches machines or computers to do what comes naturally to humans and animals: learn from previous data or experience is known as Machine learning. To learn information directly from data without relying on a predetermined equation as a model, computational methods are used by Machine learning algorithms. Based on the number of samples available for learning increases, the algorithms improve their performance.

Why Machine Learning Matters

Machine learning has become a key technique with the rise in big data for solving problems in areas, such as:


* Computational finance, for credit scoring and algorithmic trading
* Image processing and computer vision, for face recognition, motion detection, and object detection
* Computational biology, for tumor detection, drug discovery, and DNA sequencing
* Energy production, for price and load forecasting
* Automotive, aerospace, and manufacturing, for predictive maintenance
* Natural language processing, for voice recognition applications

More Data, More Questions, Better Answers
Machine learning algorithms find natural patterns in data that generate insight and help make better decisions and predictions. They are used every day to make critical decisions in medical diagnosis, stock trading, energy load forecasting, and more. For example, media sites rely on machine learning to sift through millions of options to give song or movie recommendations. Retailers use it to gain insight into their customers’ purchasing behavior.

Nusrat Jahan Momo:
Thanks for sharing.

iftekhar.swe:

--- Quote from: motiur.swe on July 09, 2018, 04:48:18 PM ---
* Computational finance, for credit scoring and algorithmic trading
--- End quote ---

can you please help me in this regard?

sagar.swe:
Yes, machine learning can help in the area  different prediction. It can much impact in the area of software engineering.

afsana.swe:
I also interested to learn more. Could you please share some more info please ?

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