Applications of Machine learning
In this page, We will learn about Applications of Machine learning, What is Image Recognition?, What is Speech Recognition?, What is Traffic Prediction?, What is product recommendations?, What is self driving cars?, What is Email Spam and Malware Filtering?, What is Virtual Personal Assistant?, What is Online Fraud Detection?, What is Stock Market trading?, What is Medical Diagnosis?, and What is Automatic Language Translation?
Applications of Machine learning
Machine learning is a buzzword in today's technology, and it's gaining traction at a breakneck pace. Even if we aren't aware of it, we use machine learning in our daily lives through Google Maps, Google Assistant, Alexa, and other similar services. The following are some of the most popular real-world Machine Learning applications:
1. What is Image Recognition?
One of the most common uses of machine learning is image
recognition. It's used to identify things like people, places,
and digital photographs.
Automatic friend tagging suggestion is a common use of
picture recognition and facial identification.
Facebook has a tool that suggests auto-tagging of friends. When we submit a photo with our Facebook friends, we get an automatic tagging recommendation with their names, which is powered by machine learning's face identification and recognition algorithm.
It is based on the "Deep Facial" Facebook project, which is in charge of face recognition and individual identification in photos.
2. What is Speech Recognition?
When we use Google, we have the option to "Search by voice,"
which falls under the category of speech recognition and is a
prominent machine learning application.
Speech recognition, often known as "Speech to text" or "Computer speech recognition," is the process of turning voice instructions into text. Machine learning algorithms are now widely used in a variety of speech recognition applications. Speech recognition technology is used by Google Assistant, Siri, Cortana, and Alexa to obey voice commands.
3. What is Traffic Prediction?
When we want to go somewhere new, we use Google Maps, which
offers us the best path with the shortest route and
anticipates traffic conditions.
It uses two methods to anticipate traffic conditions, such as whether traffic is clear, sluggish moving, or extremely congested:
Google Maps and sensors provide real-time car position.
At the same time, average time has been taken on previous days.
Everyone who uses Google Map contributes to the app's improvement. It collects data from the user and transmits it back to its database in order to improve performance.
4. What is product recommendations?
Various e-commerce and entertainment organizations, such as
Amazon, Netflix, and others, employ machine learning to make
product recommendations to users. Because of machine learning,
whenever we look for a product on Amazon, we begin to receive
advertisements for the same goods while browsing the internet
on the same browser.
Using multiple machine learning techniques, Google deduces the user's interests and recommends products based on those interests.
Similarly, when we use Netflix, we receive recommendations for entertainment series, movies, and other content, which is also based on machine learning.
5. What is self driving cars?
Self-driving automobiles are one of the most interesting applications of machine learning. In self-driving automobiles, machine learning plays a key role. Tesla, the most well-known automobile manufacturer, is developing a self-driving vehicle. It trains automobile models to recognize people and objects while driving using an unsupervised learning method.
6. What is Email Spam and Malware Filtering?
When we receive a new email, it is immediately categorized as essential, routine, or spam. Machine learning is the technology that allows us to receive essential messages in our inbox with the important symbol and spam emails in our spam box. Gmail employs the following spam filters:
- Content Filter
- Header filter
- General blacklists filter
- Rules-based filters
- Permission filters
For email spam filtering and malware identification, machine learning algorithms such as Multi-Layer Perceptron, Decision Tree, and Nave Bayes classifier are utilized.
7. What is Virtual Personal Assistant?
Google Assistant, Alexa, Cortana, and Siri, among other
virtual personal assistants. They assist us in discovering
information using our voice commands, as the name implies.
These assistants can aid us in a variety of ways simply by
following our voice commands, such as playing music, calling
someone, opening an email, scheduling an appointment, and so
Machine learning algorithms are a crucial aspect of these virtual assistants.
These assistants record our vocal commands, transfer them to a cloud server, where they are decoded using machine learning techniques and acted upon.
8. What is Online Fraud Detection?
By detecting fraud transactions, machine learning makes our
online transactions safer and more secure. When we conduct an
online transaction, there are a number of ways for a
fraudulent transaction to occur, including the use of
phony accounts, fake ids, and the theft of funds
in the middle of a transaction. To detect this, the Feed
Forward Neural Network assists us by determining whether the
transaction is genuine or fraudulent.
The output of each valid transaction is translated into some hash values, which are then used as the input for the next round. For each genuine transaction, there is a specific pattern which changes for the fraud transaction therefore, it detects it and makes our online transactions more secure.
9. What is Stock Market trading?
In stock market trading, machine learning is commonly used. Because there is always the risk of share price fluctuations in the stock market, a machine learning long short term memory neural network is used to forecast stock market trends.
10. What is Medical Diagnosis?
Machine learning is used to diagnose disorders in medical
science. As a result, medical technology is rapidly evolving,
and 3D models that can predict the exact location of lesions
in the brain are now possible.
It facilitates the detection of brain cancers and other brain-related illnesses.
11. What is Automatic Language Translation?
Nowadays, visiting a new area and not knowing the language is
not an issue; machine learning can help us with this by
transforming the text into our native languages. This feature
is provided by Google's GNMT (Google Neural Machine
Translation), which is a Neural Machine Learning that
automatically translates text into our native language.
A sequence to sequence learning algorithm, which is combined with picture recognition and translates text from one language to another, is the technology behind automatic translation.