Real World Examples Of Machine Learning
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Modern inventions like machine learning have improved many business and professional procedures as well as our daily lives.
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It's a branch of artificial intelligence (AI) that focuses on employing statistical methods to create intelligent computer systems that can gain knowledge from databases that are already available.
Image Recognition • A well-known and common application of machine learning in the real world is image recognition. Based on the intensity of the pixels in black-and-white or color photos, it can recognize an object as a digital image. • • Examples of image recognition in the real world • • Decide whether an x-ray is malignant or not. • Give a name to a face in a photo (also known as "tagging" on social media)
Image Recognition • Segmenting a single letter into smaller images will help you recognize handwriting. • Facial recognition within a picture is another common application of machine learning. The algorithm can find similarities between persons in a database and pair them with faces. Law enforcement uses this frequently.
Speech Recognition • Speaking to text is a capability of machine learning. A text file can be created using specific software programs that can convert both live and recorded speech. In time-frequency bands, the speech can also be divided into segments based on intensities. • Examples of speech recognition in the real world.
Speech Recognition • • • •
voice lookup dialing by voice appliance management Devices like Google Home or Amazon Alexa are some of the most popular examples of speech recognition software in use.
Medical diagnosis • Machine learning is beneficial. with the identification of illnesses. To identify symptom patterns, many doctors employ chatbots with speech recognition skills. • Examples from the real world for medical diagnosis • helping to develop a diagnosis or recommending a course of treatment • Machine learning is used in oncology and pathology to identify malignant tissue. Review bodily fluids
• Facial recognition technologies and machine learning are used in conjunction to scan patient photographs for characteristics associated with uncommon genetic illnesses in the case of rare diseases.
Statistical arbitrage • Using an automated trading approach called arbitrage, a lot of securities are managed in the financial sector. The tactic makes use of economic data and correlations to analyze a group of securities using a trading algorithm.
• Examples of statistical arbitrage in the real world • Trading algorithms that analyze the microstructure of a market's enormous sets of data • Find prospects for real-time arbitrage • The arbitrage approach is optimized by machine learning to improve outcomes.
Predictive Analysis
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Available data can be categorized by machine learning into groups, which are then further defined by rules established by analysts. The analysts can determine the likelihood of a fault once classification is complete.
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Examples of predictive analytics in the real world determining whether a transaction is genuine or fraudulent
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Enhance prediction methods to determine the likelihood of a fault One of the most promising applications of machine learning is predictive analytics.
• It can be used for anything, including the pricing for real estate and product development.
Extraction • With unstructured data, machine learning can extract structured information. Organizations gather enormous amounts of client data. An automated machine learning system streamlines the annotation of datasets for tools for predictive analytics.
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Examples of extraction in the real world
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Create a model to anticipate vocal cord issues.
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Providing strategies for the illnesses' detection, diagnosis, and treatment
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aid in speedy issue diagnosis and treatment for doctors
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These procedures are typically time-consuming. Yet, machine learning can follow and gather data to produce billions of data samples.
Conclusion • In the article, I have talked about a few real-life examples of Machine learning but the list doesn't end here so if you are keen to know more about it. • I would suggest you take Machine learning coaching in Bangalore, one which I like the most is the ML course by Tutort Academy, they offer courses as well like the DSA course online, Data Science, Artificial intelligence, etc.
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