Best Machine Learning Applications
Updated: Jan 17
Table of Content
The technology which is driving the world crazy these days is machine learning. The ability of the computer to learn itself by mimicking the human brain is marvelous. It is one of the most researched areas nowadays. Machine learning has eased the lives of humans in many domains. It has opened new horizons for the world. Machine Learning is now widely used in our daily lives. We have become dependent upon it without realizing it. It has several applications in almost every discipline. Here are some of the best machine learning applications.
1. Image Recognition
It is one of the widely used and most significant machine learning applications. One primary reason for the success of self-driving cars is image recognition. It makes the computer capable of detecting and identifying an object or feature in the image.
Pattern recognition, face recognition, and optical character recognition (OCR) use the image recognition principle. Face-unlock is common in mobile phones, which is a practical example of a machine learning application.
Using the OCR to understand the written documents by the computer is one machine learning application in the industry. It has enhanced the annual revenue generated by many companies. With the help of OCR, you can further design more useful products.
Many social media platforms such as Facebook, Instagram, and Snapchat use this technique to identify your pictures. Filters and tagging on your photos are prime machine learning application examples.
Apart from this, it is used in image classification for various stock photography websites such as Unsplash. It helps them to tag and describe their content conveniently. It reduces the time of photographers by proposing relevant keywords.
2. Speech Recognition
Similar to image recognition, speech recognition is another useful machine learning application example. It is the process of converting the voice into text. Other names for this technique are computer speech recognition or speech to text.
Chatbots such as Alexa, google assistant, or Cortana are some machine learning applications in business. It has lessened the physical input from the user. Due to this, the user can now give commands to the computer without moving from his place. They have become an unpaid loyal virtual assistant for many of us. They are responsible for processing the input and giving desired results to the user. They save much time for many users. They can also guide you or give advice. It is also responsible for entertaining users.
With the help of this, you can ask the computer through voice commands for
Searching documents or files on your PC
Play your favorite music
Print files of your choice
Making phone calls
Send emails and messages
You can easily search for medical records and use this in hospitals for administrative purposes. Hence serving as an excellent machine learning application in healthcare. It improves workflow by decreasing paperwork and inputting data. It has emerged as an efficient digital assistant in the healthcare niche.
3. Sentiment Analysis:
Another practical machine learning application is analyzing the sentiment and emotion of people through text. It is determining the opinion and behavior of the writer or speaker. It accumulates both speech and image recognition and some further analysis.
Its main motive is to get the feelings of the user. It captures the overall essence of the essay and explains it in one word. Decision-making applications and review-based websites are some of its common examples.
4. Security and Fraud Protection:
Security and protection from fraud have become a significant issue in 2020. Reports say that credit card fraud is expected to reach $30 billion in 2020. Machine learning in cybersecurity is trying to control this situation. PayPal is currently using an AI-based algorithm to control money laundering.
The machine learning algorithm scans every online transaction thoroughly for suspicious profiles using fraud detection solution. It helps to reduce the loss while maximizing the profit.
5. Email Spam Classifier:
One useful application of machine learning is the email classifier. It is widely used by email service providers, including Gmail, Hotmail, and Yahoo. Such a system automatically scans emails containing spam material and puts them in the spam folder.
Compared to conventional rule-based filtering, this machine learning-based approach is more accurate. It is implemented through decision tree induction or multi-layer perception.
6. News Classification:
News classification is another machine learning application in the industry. Google News uses this to rank the most related news according to your searched keyword. There is a mass volume of data available on the internet. It is growing at a tremendous rate. Getting the news of the user’s choice is indeed a tough task.
Machine learning can solve this problem quickly. It helps to provide the user with the most relevant material. Many news classification software is available. They use the support vector machine or naive Bayes technique. Through it, the user can search for any news efficiently with an immediate response.
7. GPS and Navigation:
We all use Google Maps for navigation and directions. Machine learning helps to determine the shortest route. It also predicts the upcoming traffic on the road. It also estimates the time required to reach your destination. The question is, how does it do that?
Google Maps gathers data from its users from time to time and uses it to predict all these parameters. Moreover, in-car booking apps such as Uber, also predict the approximate cost of the ride. All these are sophisticated machine learning examples in business. Many companies use these tricks to gain maximum profit.
8. Recommender System:
It is one of the most used applications of machine learning in businesses. Google and other website keep track of your search history. It then recommends the products by showing targeted ads. It is ubiquitous for you to see your searched product on Facebook and youtube ads.
E-commerce giants such as Amazon or Walmart use this technique to compel users to buy. It is a fantastic strategy to increase your sales. This marketing technique is used to keep the customers in touch and force them to buy your products. Based on your activity and likings, it helps to promote sales by showing you those services.
According to reports, more than 35% of Amazon’s revenue comes from these recommender systems.
9. Application in Healthcare:
Machine learning tools have many applications in the medical and health sector. It is used to detect a disease or cancer, therapy planning, and prediction of the disease. Many wearables are also common to give patients information regarding their heartbeat and blood pressure.
Machine learning helps to solve problems related to genetics. It also assists the doctors in examining the X-ray, MRI, and CT scans of the patient. They are also the right consulting partners for many doctors.
Machine learning is behind all this weather forecasting and making predictions of all sorts. Its sophisticated supervised learning algorithms are capable of attaining an accuracy of almost 100%. Various enterprises use this technique for decision-making. It gives them an idea of when to invest in maximizing profits. It can also make predictions on the condition of the patient in the health sector. A method like the Hidden Markov model is mostly used for prediction.
11. Application in Finance:
Machine Learning can help many companies in dealing with their finances. They can save you from online frauds and ransoms. Moreover, it can help you to predict better investment opportunities that could be beneficial for your company.
It is a machine learning example in finance. It also protects the companies that are at any financial risk. It helps them to protect themselves from any fraud by taking necessary measures. It also helps them to predict any future increase in their revenue and other stats.
12. Video Surveillance:
Machine Learning also helps to extract specific information from the video. The video contains much more information as compared to images, audio, or text. To get the part relevant to the user without the user watching the full video is quite an achievement. For this reason, an automated surveillance system is trending these days.
It can be beneficial in detecting any human presence in the video primarily related to crime scenes. There are many methods used to identify human movement and verify them in different frames.
13. 24/7 Online Support:
Recently many sites have had this online customer support chat system with quick responses. There is not any actual human being behind the scenes but a machine learning algorithm. The website representative is a chatbot generating all the messages. It is to know the opinions of the customer to use them for evaluation later.
In a nutshell, we understand how machine learning is influencing our lives. It has made our lives easy and more convenient. It has revolutionized the old methods. Machine learning is a new science that will rule the world soon. It has proved itself to be a far better solution than traditional methods. Overall, this has shown machine learning as a service.
1. What is ML Application?
ML is an application of AI where a machine learns by itself and improves from experience without being explicitly programmed.
2. What is the best programming language for machine learning?
The best programming language for machine learning is Python.
3. What is a machine learning example?
There are many examples of machine learning, such as speech recognition, image recognition, recommender system, etc.
4. What is the machine in machine learning
It indicates that the machine is learning itself with human intervention. It uses a large volume of the dataset to train itself. Training is usually done with GPUs.