Machine Learning Applications

Machine Learning Applications
In today’s technology machine learning is a hot topic and it is expanding at a fast pace. Machine learning is used by us every day and we don’t even realize it. For example, we use google maps, etc. The following are some of the real-world machine learning applications. 

1. Recognising the image
One of the most popular implementations of machine learning is image recognition. It is used to recognize objects, people, locations, digital pictures, and so on. Automatic friend tagging suggestion is a common use case for image recognition and face detection. Facebook has functionality which provides you tagging suggestion. When we upload a picture of our friends on Facebook, we automatically get a tagging recommendation with their names, which is driven by machine learning's recognition algorithm and face identification. It is dependent on the Facebook project known as "Deep Face," which is in charge of face recognition and individual identity in images.

2. Recognising Speech
When we use Google, we have the ability to "Search by voice," which falls under speech recognition and is a common machine learning tool.
Speech recognition which is also known as "Computer speech recognition" or "Speech to text," is the method of translating voice commands into text. At the moment, in a variety of speech recognition apps, machine learning applications are commonly used. Google Assistant, Cortana, Siri, and Alexa all use speech recognition technologies to respond to voice commands.  

3. Predicting Traffic
We use google maps if we want to reach some new place. Google Maps forecasts traffic conditions, tells us about the shortest way and the best road to use. We can get to know about the traffic conditions for example if the traffic is heavy, slow or clear, by using two methods: 

  • The vehicle's real-time location is determined by the Google Maps app and sensors. 
  • Around the same time, how much average time has been taken on previous days.
In order to enhance the results, it collects information from the customer and then sends it to its servers. 

4. Recommending Products
A lot of entertainment and e-commerce firms for instance Netflix, Amazon, etc commonly use machine learning for product suggestions. Due to machine learning, we begin to see advertisements for the same products which were looking at on Amazon while browsing the internet. Google uses different machine learning algorithms to consider consumer interests and then recommends products based on those interests. Google uses different machine learning algorithms to consider consumer interests and then recommends products based on those interests. Google uses different machine learning algorithms to consider consumer interests and then recommends products based on those interests.

5. Virtual personal Assistant
We have a variety of automated personal assistants, including Google Assistant, Alexa, Cortana, and Siri. They, as the name implies, assist us in seeking facts by using our voice commands. We can use these assistants to assist us in a variety of ways simply by responding to our voice commands for instance "call someone," "schedule an appointment," or "play music" and so on. Machine learning algorithms play an important role for these virtual assistants. 
The above assistants record our voice commands, send them to a cloud server, translate them using ML algorithms, and then behave likewise. 

6. Trading in Stock Market
In the stock market, machine learning is commonly used. Since there is always the possibility of share price fluctuations in the stock market, this long short-term memory computer model of machine learning is used to forecast stock market patterns and trends. 

7. Detecting online fraud
By detecting fraudulent transactions, machine learning is making our online transactions safer and more stable. There are many possibilities for a fraudulent transaction to occur when we make a transaction online. For example, fake ids, false accounts, and in a middle of a transaction, theft of money. 

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