Categories: Machine learning

Top 30 Applications of Machine Learning in daily life

Machine Learning is simply a branch under artificial intelligence. It is all about an IT system being able to independently discover solutions to issues by just mere recognition of patterns in databases.

But before machine learning performs its responsibilities, an individual trying this out must have put in the needed algorithms, and data must be provided into the systems in advance and there must be a clear definition of the independent analysis rules for recognizing patterns in the data stock.

Do you know how machine learning work? Machine learning simply performs the task by identifying and differentiating objects after data must have been inputted.

It represents a buzzword in the world of technology today and the need for machine learning applications and engineers are on the uprise lately, we will be discussing some of the top Applications of Machine Learning in daily life you can find around today.

1. Traffic Alerts (Maps)

Advance in Technology has made life easier in the sense that you won’t need to waste time trying to get a solution to a problem. We all use google map to get the location where we are heading to conveniently.

Google Adds Traffic Alerts To Maps

Features:

  • We use it as an assistance when we need directions and when in traffic
  • It helps in predicting the upcoming traffic after which you might have inputted your location, average speed, and route

2. The Integration of Machine Learning into Facebook

Facebook uses machine learning for automatic Friend Tagging Suggestions. How does this work? Facebook makes use of face detection and image recognition to automatically look for the faces that match its database and provide us a suggestion to tag the persons with these faces.

Auto friend tagging suggestion

Features:

  • It doesn’t seem restricted to Facebook only, other platforms can find it useful too
  • It is simply all about recognizing and identifying the faces of the people in a particular picture

3. Transportation and Communicating (Uber)

These days we now book cabs on our smartphones or other devices through the internet – anyone that has done this before in one way or the other into machine learning already.

How Uber made its redesigned application smarter with machine learning

Features:

  • This application detects your location based on your travel history and patterns

4. Products Recommendations

Google tracks our search history and recommends ads for us based on our search history. This is why it is very much possible for you to search for a product on platforms like Amazon and see the ad of that product on every other platform like Facebook, YouTube, etc. you log-in to afterward.

Products Recommendations

Features:

  • A really nice machine learning application

5. Virtual Personal Assistants

These applications help us in finding good and needful information whenever we asked for it through text or voice.

Virtual Personal Assistants creation Using Artificial Intelligence

Features: The applications in this category include

  • Speech Recognition
  • Speech to Text Conversion
  • Natural Language Processing
  • Text to Speech Conversion

6. Self Driving Cars

The integration of machine learning in self driving cars is one of the coolest machine learning applications. Tesla is one of the popular companies that produce this set of cars.

Deep Learning for Self-Driving Cars – Towards Data Science

Features:

  • An excellent machine learning application

7. Dynamic Pricing

It is no news that pricing has been a major problem when it comes to paying for a good or service. Setting out the right price has always been an issue. Dynamical pricing of any of these commodities is one of the goods ways of getting this issue right.

Dynamic pricing: In-depth Guide to Improved Margins [2020]

Features:

  • You now have the opportunity to track buy trends and deduce more competitive product prices due to the advent of artificial intelligence
  • Uber effectively uses this machine learning application well

8. Google Translate

This application comes in handy when people love visiting places that speak different languages. GNMT, known as Google Neural Machine Translation is a Neural Machine Learning that has support on many several languages and dictionaries. GNMT makes use of  Natural Language Processing in offering the perfect translation of sentences or words.

Machine Learning Translation and the Google Translate Algorithm

Features:

  • It helps to ease communication among people of different languages

9. Netflix: The Online Video Streaming Application

It is actually looking like a one-man race in favor of Netflix in all matters that have to do with the online streaming of videos. If you may ask how are they able to achieve this, the integration of machine learning on Netflix has been helping them to stand out among others.

Netflix Machine Learning Infra for Recommendations – 2018

Features:

  • The Netflix algorithm frequently collects huge amounts of data about the activities of its users.

10. Fraud Detection

Machine learning fraud detection is one of the most important applications that must be fully implemented on every platform. The machine learning model extensively x-rays the transactions of customers in an attempt to see if there is a suspicious pattern.

LinkedIn
Machine Learning for Fraud Detection

Features:

  • Fraud detection is regarded as a classification problem in machine learning

11. Healthcare and Medical Diagnosis

The practitioners in the medical line make use of machine learning in predicting the progression of a disease, extracting health-related knowledge for outcomes research, the management of patient health conditions, etc.

Machine Learning in Healthcare – Learn the advanced machine …

Features:

  • It is a very good tool for analyzing clinical parameters
  • It is also used for data analysis of healthcare-related records

12. Commute Predictions

In commuting predictions, we mean it in the sense of predicting traffic and also using machine learning for online transportation applications. These two attributes under this category have proven to be very important in our day to day life.

Prediction based traffic management in a metropolitan area …

Features:

  • This has been helping us to avoid traffic and where we plan to go on time
  • It also helps us to predict the price and Electronic Travel Authorization on our cab booking applications

13. Social Media

The integration of machine learning on social media platforms has made users more active and familiar with social media. We have able to make effective use of these platforms due to machine learning.

Machine Learning: Make Social Media Management Smarter – Exadel

Features:

  • Machine learning has been playing a crucial role in the creation of user-friendly social media websites and applications

14. Human Detection Artificial Intelligence Software

Many software applications these days now use machine learning for Friends Suggestion and Face Recognition on their various platforms. Examples of these platforms are Facebook, Instagram, etc.

Image Detection, Recognition, and Classification with Machine Learning

Features:

  • Popular social media platforms quickly recognize our friends immediately we upload the picture on media and start giving notifications to tag them
  • The use of machine learning also enables Facebook to suggest to us likely friends we can connect with

15. Optimization of Search Engine Results

Many search engines like Google make use of machine learning in improving their search results.

Search Engine Journal
How to Build Your Own Search Ranking Algorithm with Machine Learning

Features:

  • Algorithms study the way we relate or interact with the results shown to us

16. Video Surveillance and Security

If we are being honest, it is never easy for a person or a quite few number of individuals to keep track of many surveillance cameras at the same time. Machine learning trained surveillance cameras have come in handy to make things less difficult by recognizing the possibility of a crime before it occurs.

Memoori
Webinar: Machine Learning Making Video Surveillance Smart

Features:

  • These smart cameras immediately alerts the personnel human attendants if they have recorded any possibility of a crime

17. Cyber Security

Machine learning has been doing a lot in giving a potential insight in helping to curb the fraudulent activities that are concerned with money online.

Machine Learning for Cyber Security

Features:

  • PayPal and other common banking applications make use machine learning in keeping track of transactions
  • Machine learning can also play a big role in separating legitimate transaction from illegitimate ones

17. Customer Service

Machine learning programmed chatbot has been working nicely as a customer care representative on websites these days.

Algorithmia
Vertical Spotlight: Machine Learning For Customer Service …

Features:

  • It has been helping customers in providing solutions to their queries
  • Machine learning algorithms have been playing a big role in improving the capability of the bots
  • Bots provide answers to users’ queries by collecting information from the data store of the website

18. Email Spam

Machine learning algorithms have been helpful in ensuring security and providing the latest updates to the spam filtering approaches used by email clients and many other applications in our world today.

ScienceDirect.com
Machine learning for email spam filtering: review, approaches and …

Features:

  • Common filtering techniques include Perceptron, C 4.5 Decision Tree, etc.

19. News Classification

News classification is another good application by machine learning. As a matter of fact, this has been helping one way or the other in increasing the number of useful information on the web these days.

KDnuggets
Automated Text Classification Using Machine Learning

Features:

  • Common machine learning methods used for News classification software include vector machine, naive Bayes, k-nearest neighbor, etc

20. Classification

Classification has to do with the arrangement of objects or instances into a collection of predetermined classes. The goal of machine learning in this category is to dynamize classier systems.

Towards Data Science
Machine Learning Classifiers – Towards Data Science

Features:

  • Machine learning has been helping in improving the efficiency of classier systems

21. Author Identification

Author identification can also be referred to as Authorship identification. This has been used in putting a stop to unlawful use of online messages for illegal motives.

ScienceDirect.com
Naïve Bayes classifiers for authorship attribution of Arabic texts …

Features:

  • The authorship identification may find the likes of criminal justice, academia, and anthropology, etc. useful

22. Regression

Regression also makes adequate use of machine learning. It has been playing a big role in providing outputs based on the objects inputted in regression.

ResearchGate
Machine learning and prediction of oxidation potentials by two …

Features:

  • Machine learning has been providing support in optimizing parameters in regression

23. Age/Gender Identification

Age or gender identification can’t be denied its importance. Machine learning and artificial intelligence can be effectively used in making age/gender identification.

Learn OpenCV
Gender and Age Classification using Deep Learning | Learn OpenCV

Features:

  • SVM classifier is essential in this category

24. Language Identification

Language identification is also popularly known as language guessing. It is all about recognizing a particular kind of language. Machine learning and artificial intelligence are one of the best ways of carrying this out.

Features:

  • Common examples of Language Identification are Apache OpenNLP, Apache Tika, etc.

25. Information Retrieval

Information Retrieval is the extraction of knowledge or structured data from the unstructured ones. The use of machine learning and artificial intelligence in Information Retrieval has proven to be one of the best among others so far.

ResearchGate
2 Text categorization between machine learning and information …

Features:

  • Information Retriever has been adequately utilized in the big data sector

26. Robot Control

Machine learning algorithms have been playing a hugely significant impact on the robot control system.

Emerj
Machine Learning in Robotics – 5 Modern Applications | Emerj

Features:

  • The scope of artificial intelligence in robotics includes vision, motion control, grasping, data, etc.

27. Automatically Adding Sounds To Silent Movies

The system in this regard will have to synthesize sounds in order to come out with a match for silent movies.

MIT News
Artificial intelligence produces realistic sounds that fool humans …

Features:

  • It supports convolutional neural networks and Long short-term memory (LSTM) recurrent neural networks (RNN)

28. Automatic Text Generation

Many writings are provided here and from the corpus, a lot of texts can be generated. Depending on how they want it done, you can be words-by-words or characters-by-characters.

ResearchGate
Generic Automatic Text Summarization Process

Features:

  • It can learn how to spell, punctuate, form sentences
  • This model can also capture the writing style in the corpus

29. Predicting Earthquake

Computers have been taught how to use Deep Learning to know viscoelastic computations. These particular computations are used for predicting earthquakes.

Towards Data Science
Earthquake Prediction with Machine Learning

Features:

  • The application of this can be used to save lives

30. Advertisement

Advertisers (including publishers) have been making adequate use of Deep Learning in boosting their ads in order for them to remain relevant and for improving the return on investment of their advertising campaigns.

Amazon Web Services
Machine Learning for Advertising

Features:

  • A very good tool for advertising products and services

Conclusion

In this article, we saw Applications of Machine Learning in daily life. It is possible that the study here might have experience with techniques like Supervised Learning, Unsupervised Learning, and Natural Language Processing.

Majority of points given here one way or the other talk about the latest updates and technical strategies in Artificial Intelligence & Machine Learning like Deep Learning, Graphical Models, and Reinforcement Learning used in daily life.

Olanrewaju Olakunle

Mobile Software Developer, Copywriter and a Sports Analyst.

Published by
Olanrewaju Olakunle

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