Top 10 Machine Learning Applications in Real World
Machine learning is the hottest buzzword in technology today, and it’s growing rapidly. Machine learning is a part of our everyday lives, even though we don’t know it. Here are the top-rated real-world applications of machine learning uses.
Top 10 Applications of Machine Learning
1. Image Recognition
One of the most popular applications of machine learning is image recognition. It can be used to identify people, objects, and digital images. For image recognition and facial recognition. Automatic friend tag suggestion.
Facebook offers an auto friend tagging feature. When we share a photo on Facebook with friends, we get an automatic tagging suggestion with the name. The technology behind this feature is machine learning’s facial detection and recognition.
It is based upon the Facebook project ” Deep Face”, which is responsible for face recognition and person identification.
Also read: The Expansive Reach of Machine Learning
2. Speech Recognition
Google offers the option to “Search by Voice” which is a popular machine learning application.
Speech recognition refers to the conversion of voice instructions into text. It is also known as ” Speech-to-text” or ” Computer speech recognition”. Machine learning algorithms are used in many speech recognition applications. Google assistant Siri Cortana and Alexa use speech recognition technology to interpret voice commands.
3. Traffic prediction
Google Maps is a great tool for finding the best route to a new location and predicting traffic conditions.
It can predict traffic conditions, such as how clear, slow-moving, or congested, using two methods:
- Location in Real-Time of the vehicle from Google Maps app and sensors
- In past days, average time took.
Every person who uses Google Maps helps to improve the app. It collects information from users and returns it to its database to improve performance. This application of machine learning example is used for daily life.
4. Product recommendations
Many e-commerce and entertainment companies use machine learning to recommend products to users, such as Amazon and Netflix. Machine learning is responsible for the fact that we get an advertisement for the exact same product every time we search Amazon for a product.
Google uses machine learning algorithms to understand user interests and recommends products that match customer needs.
Similar to the previous, Netflix also offers recommendations for movies and entertainment series. This is done using machine learning.
5. Self-driving cars
Self-driving cars are one of the most fascinating applications of machine learning. Self-driving cars are a major application of machine learning. Tesla, the world’s most well-known car manufacturer is currently working on a self-driving vehicle. The unsupervised learning method is used to train car models to recognize people and objects as they drive.
6. Email Spam and Malware Filtering
Every email we receive is automatically filtered as spam, normal, or important. Machine learning is the technology behind receiving important emails in our inboxes. It includes the important symbol as well as spam emails in the spam box. Here are some spam filters that Gmail uses:
- Content filter
- Header filter
- Filter for general blacklists
- Filters based on rules
- Permission filters
For email spam filtering and detection, some machine learning algorithms, such as Multilayer Perceptron and Decision Tree, are used.
7. Virtual Personal Assistant
There are many virtual assistants available, including Google Assistant and Alexa. Cortana and Siri. They help us find the information we need using our voice instructions, as their name implies. With our voice instructions, these assistants can assist us in many ways. For example, they can play music, call someone or open an email. Scheduling appointments, scheduling an appointment, and so on.
These virtual assistants make use of machine learning algorithms.
The assistants record our voice instructions and send them over the cloud to a server. They then decode it using ML algorithms and act accordingly.
8. Online Fraud Detection
Machine learning detects fraud transactions and makes online transactions safe and secure. There are many ways in which a fraudulent transaction could occur online. These include fake accounts and fake ids. Steal money can also be made during an online transaction. Feed-Forward neural network assists us in detecting fraud transactions and authentic transactions.
Each genuine transaction’s output is converted to hash values. These values are then used as input in the next round. Each genuine transaction has a pattern that is used to detect fraud transactions.
9. Stock Market trading
Stock market trading is a popular use of machine learning. Stock market volatility is a constant threat. Machine learning’s short-term memory neural network can be used to predict stock market trends.
10. Medical Diagnosis
Machine learning is used in medical science to diagnose diseases. Medical technology is rapidly developing and can now create 3D models that predict the exact location of brain lesions.
It makes it easy to find brain tumors or other brain-related disorders.
11. Automatic Language Translation
Today, it doesn’t matter if we go to a foreign place and don’t know the language. Machine learning can help us convert the text into our familiar languages. This feature is provided by Google’s GNMT (Google Neural Machine Translation), which is a Neural Machine learning that translates the text into our language. It is also known as automatic translation.
The automatic translation uses a sequence-to-sequence learning algorithm. This is combined with image recognition to translate the text from one language into another.