Whenever we hear about machine learning, we feel very great, complicated, and perhaps not having physical presence, conjuring up images of futuristic robots taking over the world. As more organizations and people rely on machine learning models to manage growing large data, instances of machine learning are occurring in front of and present around us—whether we notice or not.
What’s exciting to see is how it’s improving our quality of life, supporting in terms of efficiency and more effective execution of some business operations and industries, and uncovering patterns that humans are likely to miss. Below are some Machine Learning Uses At Different Domains.
Machine Learning Uses At Different Domains
1. Facial recognition
Facial recognition is most used applications of machine learning. Did you know how we get name suggestion of our friend just by putting their images and Facebook tagging? now a days if we click picture with our friend on Facebook than it will tag that person automatically.
It has become highly useful in healthcare to help and detect genetic diseases or track a patient’s use of medication more accurately. it also used in social issues such as child sex trafficking or sexual exploitation of children.
2. Product recommendations
Have you ever wonder how we are getting product recommendation or item recommendation ;all this credit goes to machine learning!
Here retail uses machine learning to group customers based on buying habits or demographic similarities, and by liking of what one person may want from someone else’s purchases i.e. we have seen as ‘you may also like’ in this some suggested purchase pairings are obvious, it become easy for machine learning to give customer what they were looking for. Sometime if we go and buy some product than also, we get that product in recommendation this may be sometime not liking to user but any ways machine learn from all this activities
3. Email automation and spam filtering
Machine learning has given its effect on Email automation process. It is a result of successful machine learning, major function as we can see is spam filtering. Spam filtering and text recognizing to put on spam This includes data from email domains, a sender’s current location message text and structure, and obviously IP addresses. marking on the email is also help machine learning to grow, with each marked email, a new data reference is added that helps with future accuracy.
4. Financial accuracy
Machine learning has created a boon for the financial industry as most systems are on go digital. Abundant financial transactions that can’t be monitored naked eyes but can be easily analysed with the help of machine learning, which helps find fraudulent transactions. One of the newest banking features is the ability to deposit a check straight from your phone by using handwriting and image recognition to “read” checks and convert them to digital text/signature. Credit scores and lending decisions are also powered by machine learning as it both influences a score and analyzes financial risk.
Additionally, combining data analytics with artificial intelligence, machine learning, and natural language processing is changing the customer experience in banking.
5. Social media optimization
Platforms like Facebook , Instagram and Twitter are using big data and AI(artificial intelligence) to advance their functionality and strengthen the user experience. Machine learning has help in fighting inappropriate content and cyberbullying, one of the important thing while hacking is to learn from user activity .which pose a risk to platforms in losing users and weakening brand loyalty. Processing data through deep neural networks also allows social platforms to learn their users’ preferences as they offer content suggestions and target advertising.
6. Healthcare advancement
Now a days we also make appointment online and have a medical records That means healthcare information for clinicians can be improve with analytics and machine learning to gain insights that support better planning and patient care, improved diagnoses, and lower treatment costs. Healthcare brands such as Pfizer and Providence have begun to benefit from analytics enhanced by human and artificial intelligence.
There are some processes that are better suited to leverage machine learning is leading to earlier detection of abnormalities or heightened attention on concerning areas. In the long run, machine learning will also benefit family practitioners or internists when treating patient’s bedside because data trends will predict health risks like heart disease.
7. Mobile voice to text and predictive text
Machines are also capable of learning language in other formats. You may be aware of Siri and Cortana, voice-to-text applications learn words and language then transcribe audio into text. Predictive text also deals with language. here supervised learning trains the process to recognize and predict what common, contextual words or phrases will be in use based on what’s written. Unsupervised learning goes further, adjusting predictions based on data.
conclusion
You may start noticing that predictive text will recommend personalized words. For instance, if you use some word which are not present in dictionary than it will learn and add to it than when you again ask for that it may give you the result that you were searching for. it is very good practice Machine Learning Uses At Different Domains so that conversation will not be unidirectional.
written by: Nikesh Maurya
Reviewed By: Krishna Heroor
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