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Machine learning is a branch of artificial intelligence that focuses on creating systems that learn and evolve based on the data they receive. Self-driving cars and voice assistants on smartphones are technologies based on machine learning. Self-driving cars use computer vision technology. Voice assistants use speech and sound recognition technology.
What is machine learning used for? Here are some of them
Let’s look at some examples of how machine learning is being used.
1. Manufacturing
- Robotics solutions;
- Production management systems;
- Resource management;
- Anomaly and defect detection;
2. Retail
- Prediction of customer behaviour
- Logistics optimisation;
3. Legal services
- Search for relevant cases;
- Contract analysis;
4. Transport
- Logistics
- Shipping;
5. Oil and gas
- Search for natural resources;
- Making recommendations to reduce production losses;
6. Agriculture
- Monitoring soil, plant health, water evaporation, etc;
- Making recommendations for works;
- Use of robotics;
7. Media
- Content analysis and generation;
- Protection of intellectual property;
8. Financial services
- Investment portfolio optimisation;
- Fraud detection;
- Risk prediction.
Virtual personal assistants
All smartphone owners have come across them in their daily lives. They help us in many cases. For example, you can ask them to dial a specific phone number, play music, etc. How does it work? The voice assistant records your command and sends it to the server, usually located in the cloud. The request is then processed using machine learning and neural networks, and you get the result. If you’ve noticed that these services don’t work well without the internet, it’s because the connection to the server is lost.
Traffic Forecast
When you plot a route on Google Maps, you can see where traffic is heavy. How does Google learn about road conditions? Thanks to machine learning. To determine congestion, it takes into account the average time spent on a particular route on certain days and at certain times, as well as data on the location of vehicles gathered from GPS sensors.
Social media personalisation
You’ve been online looking for a new smartphone. In the future, when you visit Facebook, you will see ads for smartphones. You will also see them on YouTube and Instagram. Using machine learning, Google has identified that you are interested in buying this gadget. So this ad is only targeted at you.
Assistive medical technologies
Medical technology has been updated through the use of machine learning. We can analyse two-dimensional CT scans and create three-dimensional models that suggest and predict where exactly in the brain there is damage. Machine learning could potentially transform areas of medicine such as disease detection, personalised treatment, clinical research and more.
Machine learning in business
Artificial intelligence is increasingly seen as a tool to help optimise business processes and reduce costs. This software can make decisions and take action on its own, even in situations not originally anticipated by the developers. For example, to detect a new type of fraud.
Algorithms can be used to price and forecast goods and services, predict customer behaviour, calculate sales forecasts, etc.
Stock market trading
Machine learning is widely used in stock market trading. Stock market indices such as the NIKKEI use the long short-term memory of neural networks to classify, process and predict data.
Machine Learning by Filio Force Inc.
The main difference between machine learning and standard algorithms is its adaptability, as it is constantly evolving and learning. The more data an algorithm consumes, the more accurate its analysis and predictions become. Machine learning allows the computer to learn about similar situations, build chains of logic and form new solutions. Applying machine learning in business allows you to optimise costs, identify weaknesses and improve workflows. If you would like to implement machine learning technologies in your business or any other type of activity, please contact Filio Force it company through the contacts listed on the company’s website.
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