20+ Examples of Machine Learning (ML) in Real Life

Hi Friends! Today, we are going to explore about various simple real-world examples of machine learning in detail with ease. At the end of this article, you will definitely completely educate about several real-life machine examples without getting any hassle.

Overview of Machine Learning

Today, machine learning technology has becoming one of the greatest milestones of the Hi-Tech industry. It is going to adopt in the banking & financial domain, medical & healthcare sector, smartphone, and etc. The main goal of the ML is to simulate human thinking and perform the behaviours by recognizing pattern and automation processed that has the frequently surpass the abilities of human beings.


Machine learning is a subset of the Artificial Intelligent that getting to focus on the using of statistical technology to develop the intelligent computer systems to learn from the available databases.

Machine Learning Examples Tutorial Headlines:

In this section, we will show you all headlines about this entire article; you can check them as your choice; below shown all:

  1. Overview of Machine Learning
  2. Are You Finding for Examples of Machine Learning?
  3. How Many Types are Machine Learning?
  4. Examples of Machine Learning in Daily Life
  5. FAQs (Frequently Asked Questions)
  • Is Netflix an example of machine learning?
  • Why is machine learning important examples?
  • What are the real world examples of machine learning?
  • Is Siri machine learning?

Let’s Get Started!!

Are You Finding for Examples of Machine Learning?

Machine learning adopts the statistical approaches to enhance the computer’s intelligence that is giving the assistance in the automation utilization of all business data. Cause of growing the reliability on machine learning technologies, then lifestyles of the human have undergone the intensively transformation. We are getting to use the subset of artificial intelligence, whether consciously or unconsciously. Google Assistance is a real-life example; it adopts the machine learning principle.

How Many Types are Machine Learning?

Before going into the many examples of machine learning in the daily-life, you should be known about some brief detail to four key machine learning types along with examples; below shown each on, you can check them:

Also Read: Different Types of Machine Learning With Examples!

Supervised Learning: In this type of ML, we can feed the output of algorithms into the system that machine get to know the pattern before the working on them. That means, the algorithms gets trained on the input data that has been made to label for the specific output.

Semi-Supervised Learning: This machine learning adopts the combination of a less amount of labelled data and the enlarge amount of unlabelled data to get train models. This approach enables with supervised machine learning by using the labelled training data and the unsupervised learning that uses the unlabelled training data.

Unsupervised Learning: This approach is amazing for the uncovering relationships and insights in unlabelled datasets. The models feed input data along with unknown desirable outcomes. Therefore, the inferences are constructed based on the circumstantial evidence without having the training otherwise guidance.

Reinforcement Learning: In this approach, the machine learning is getting to determine the best path otherwise option to choose in the situation to maximize the reward. The key example is the video games.

Examples of Machine Learning in Daily Life

In this section, we are going to cover 20 real world examples of machine learning in detail; and you should be known about them, below mentioned each one, you can check them:

Also Read: 25 Advantages and Disadvantages of Machine Learning | Pros and Cons

Virtual Personal Assistants:

Today, we are going to use many virtual personal assistance like as Alexa, Cortona, Siri, and Google assistance. With helping of them, user can find the any information by using own voice instruction. These assistance lets users help to use in many ways only by own voice instructions like as call to someone, open the email, play music, scheduling an appointment and more. This assistance records our sound instruction, move it to server over the cloud and decode it by helping machine learning algorithms and perform its tasks perfectly.

Videos Surveillance:

The video surveillance is the most eminent example of the machine learning that helps to detect any offence before it occurs. It is the most sufficient as compare to observe by the human, because it is more difficult and boring work for the human to keep monitoring on several video at once. Then, video surveillance is most helpful as they keep monitor on certain behavior of the person such as keep standing motionless for a longer time duration, napping on benches, stumbling, and so on. If, the video surveillance system searches any unusual activity, it pushes the respective team, which is capable to stop otherwise help prevent few miss happening at that place. Today, the video surveillance is going to use in many areas like as: Facility protections, Operation monitoring, Parking, Traffic monitoring, shopping patterns and etc.

Image Recognition:

Image recognition that makes deal with cataloging and identify the feature otherwise an object in the digital picture. This is not important and focus able machine learning and Artificial Intelligence technology. This concept works with for many further analyses like as face detection, face recognition and pattern recognition.

Social Media Services:

The social media companies are also using the machine learning for their own and user benefits, as well as customizing your news feed to get excellent ad targeting.

Facebook: Facebook adopts the ML and AI to detection of faces. When you are uploading the picture on FB, then it will get automatically reflects the faces and suggests friends tag. Moreover them:

  • It appears the ad of a specific business that is most relevant to uses’ interest.
  • It allows personalizing the news feed and making ensure to reflect posts that amuse one.

Snapchat: It serves the facial filter namely with ‘Lenses‘ that filter and keep track the all activity, permits the users to tag with animated pictures otherwise digital masks that can shift whenever their faces move.

Instagram: By using the machine learning algorithms, sentiments behind the emojis can be easily identified. IG also allows users make and auto-recommend emojis and its hash tags. There is the vast utilization of emoji across the all demographics that are going to use with describing and explore by IG at the huge scale via emoji-to-text translation.

Pinterest: It will get employ computer vision to automatically recognize object in the picture or ‘Pin’ and then recommend identically pins. It is also cover the spam prevention, discovery, email marketing, ad performance, and search along with using the ML and AI.

Traffic Alerts By Using Google Map:

Whenever, you are going to new place for vacations, then you can take assistance of Google Maps that shows you the perfectly path along with the shortest route and give the prediction of traffic conditions. If traffic conditions as per prediction are traffic is cleared, slow moving or heavily congested along with helping of two ways:

  • It shows the real Time location of the vehicle from sensors and Google Maps.
  • It takes the average time on past days at the same time duration.

Each one who is adopting the Google Map is assisting this app to make it better. It takes the information from the user and sends back to its database to enhance the performance

Email Spam & Malware Filtering:

When, you receive the multiple emails, then it is filtered automatically as normal, spam, an important. It is also most popular example of the machine learning and AI. By helping the ML algorithms, you always receive the important email on your inbox along with the important symbol and spam emails in your spam box. There are few spam filters that are used by Gmail like as: Content Filter, Header filter, General blacklists filter, Rules-based filters, and Permission filters.

Few machine learning algorithms are going to use in the email spam filtering and malware detection along with Decision tree, Naïve Bayes classifier, and Multi-Layer Perceptron.

Online Customer Support:

Now these days, most of websites serve the option to chat with customer support representative, while they are getting to navigate within the websites. But, it is not possible to each website has a live executive to give replay your question. So, most of time, you talk to a Chabot. These bots helps to extract the information from your website and show it to the customers. Hence, the Chabot is getting more popularity with this time. They are able to understand the user queries better and offer them along with excellent answers. This is possible cause to its ML algorithms.

Speech Recognition:

Google allows user the best feature that is ‘Search by Voice’. It is a good example of speed recognition. In the speech recognition process, to convert the voice instruction into text format that is also called the ‘speech to Text’ otherwise ‘computer Speech Recognition’. Now these days, machine learning algorithms are mostly working in several areas of speech recognition like as Alexa, Cortana, Siri, and Google assistance; in which to use the speech recognition techniques to follow the sound instructions.

Search Engine Result Refining:

Most of all search engines (Google, Bing, Yendex, and etc.) adopt the machine learning technology to enhance the search results for their users. Each time you find any information with executing keywords, then algorithms at the backend keep a watch at how you gets respond the results. When, you open the top result and stay on the web page for longer time, the search engine assumes that this results is shown were at the depend on query. Same as; when you reach the second or 3rd page of the search results but do not open any results. Then, search engine gets estimation that the result offered did not perfectly match requirement. Hence, ML algorithms are working at the backend for improving the search results.

Get Automation as Employee Access Control:

Large scaled firms are going to adopt the machine learning algorithms to identify the level of getting to access employees would need in several areas; it depends on their job profiles. It is also one of the coolest examples of machine learning.

Product Recommendations:

Product recommendation is one of the most examples of the machine learning. Product recommendation works as the stark features of most of each e-commerce web portals today. By helping of machine learning, website lets you know about your behavior based on your last purchases, cart history, searching pattern and then make deal with the product recommendations.

Stock Market Trading:

Today, Machine learning is widely using in share marketing trading. In the share market, there is always getting a risk of up and down in the stock. Therefore, this machine learning’s long short term memory neural network is adopted for the prediction of share market trends.

Banking and Financial:

Today, banking and other financial firms are going to adopt the advanced technology that is machine learning. ML helps to their clients for getting to prevent fraud and protect account from the unwanted activities. The machine learning algorithms identify that what factors to consider making the filter to keep harm at bay. Most of websites, which are unauthentic will be automatically filtered out and most restricted from the initiating transactions.

Cyber Security:

GPay and PayPal are also good examples of machine learning that help to track the transactions and differentiating in between the illegitimate and legitimate transactions. Hence, machine learning allows to get sound cyber security by preventing the online monetary fraud.

Environment Protection:

Machine learning algorithms also help to boost up the environment sustainability. For the good example: is IBM’s Green Horizon Project, in which the environment statistics from assets and sensors are getting to leverage to generate the pollution forecasts. The main objective is to bring down the environment bad impacts.

Automatic Language Translation:

This is also one of the most common machine learning examples is the language translation. Machine learning plays the major role into translation of language translation one to another. We are stunned that how the websites are capable to translate from one language to another and provide the contextual meaning as well. Behind of this, one translation tool is working that is known as the ‘Machine Translation’. It allows to people to make interaction along with others from all around the world. Without helping it, life would not be easily as it is now. It has offered the confidence to travelers and business man to safely venture into out of country along with conviction that language will no longer be a limiter.

Auto-Friend Tagging Suggestion:

It is also one of the eminent examples of the machine learning is the Auto-friend tagging suggestions service by offering Facebook. When we try to upload a new image on the FB along with friend, then it suggest to tag the friend and automatically offers the names. FB performs it by helping the DeepFace that is a facial recognition system made by Facebook. It is capable to get identify the images and faces as well.

Healthcare & Medical Diagnosis:

Machine learning makes deal with many techniques and tools along with diagnostic and prognostic problems in the diverse medical realms. The machine learning is widely going to use for many areas in the medical like as:

  • Exploring the data generated by the medical units
  • Effective monitoring of patients
  • Keep handling the inappropriate data
  • To analysis of medical data for identify the regularities in the data

The ML also gives the assistance for estimating disease breakthroughs, planning and assisting therapy, driving medical data for yielding the research, and fully patient management.

Home Security and Smart Homes:

Powered alarms and cameras are now getting the forefront cutting edge home protection. These kinds of security systems always adopt the facial recognition program and machine learning techniques to establish a catalog of your home’s regular visitors. It lets the system to detect the uninvited guests. This also allows to track whenever you last time walked with your dog or notifying when your kids are come back home from school. Few are modern system can get automatically make call emergency services.

Cloud Services:

The Amazon’s cloud service AWS offers the free of cost machine learning services and product to assist the data scientists and developers build train and deploy the customized ML models. AWS also provides the Amazon Recognition that adopts the machine learning to identify objects, people, text and perform activities into the both videos and pictures.

FAQs (Frequently Asked Questions)

Is Netflix an example of machine learning?

Today, Netflix’s service is getting more popular over the world is that the company adopts the cutting edge technology such as machine learning and artificial intelligence to offer the consumers along with suitable and intuitive suggestions.

Why is machine learning important examples?

Machine learning examples are most important because they provide the enterprise a view of trends in the customer behavior and business operational pattern, as well as getting to support the design of the new products.

What are the practical examples of machine learning in real world?

In this post, already we have been explored above many simple real world examples of the machine learning in detail; you can show them.

Is Siri machine learning?

Yes! It adopts the advanced machine learning technologies to function.

The Bottom Lines

Now i hope that you have been fully learnt about many real-world examples of machine learning with ease. If this post is helpful for you, then please share it along with your friends, family members or relatives over social media platforms like as Facebook, Instagram, Linked In, Twitter, and more.

Also Read: 35 Applications of Machine Learning | Uses of Machine Learning in Daily Life

If you have any experience, tips, tricks, or query regarding this issue? You can drop a comment!

Happy Learning!!

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