This article will showcase examples of the application of machine learning in the real world. While the topic of machine learning may seem inaccessible to the non-technical user, it is shaping a lot of the world that we live in today. Machine learning can be used in any field where data is involved.
Here are real-world examples of the application of machine learning:
1. Image Recognition
Image recognition, a subset of machine learning, enables computers to analyze and understand visual data. It has real-world applications in fields like healthcare, retail, autonomous vehicles, agriculture, and more, ranging from medical diagnoses to cashier-less stores and autonomous driving.
Using machine learning to tackle climate change and monitor biodiversity.
Another key machine learning task is the classification. It involves assigning data to categories or classes. In practice, it’s used for spam email filtering, sentiment analysis in social media, and identifying diseases from medical images, among many other applications.
Documents, Images or Videos are often classified using machine learning (document clusters, recommender systems).
3. Forecasting and Predictive Analytics
Forecasting in machine learning helps predicts future trends and values based on historical data. It finds extensive use in E-Commerce, SEO, stock price prediction in finance and weather forecasting. For example, Facebook uses machine learning to predict a person’ likelihood to click on an ad (source).
4. Information Retrieval
Search Engines can use machine learning in their information retrieval systems to help satisfy the user better, but also to improve the efficiency of crawling, indexation and serving of content.
Google, for example, uses machine learning classifiers to identify helpful content or even spammy content to promote or demote in their search results.
5. Image Generation
Image generation in machine learning is used to create artificial images through generative models. It’s used by website owners for creating creative visuals or by gaming and animation organizations for creating realistic images.
Here is an example using DALL-E
6. Video Generation
Video generation in machine learning is used to generate dynamic sequences of images (e.g. video). It is often used for creating animations, video effects, or synthesizing realistic video content.
In this example, Facebook’s “Make-A-Video” generates videos from text.
7. Music Generation
Music generation in machine learning involves creating or composing music using algorithms and models. It has started being used in music production for creating new tunes, creating background music for videos and games and to enhance the user experience in streaming platforms.
For example, Soundraw.io creates music using machine learning systems.
It is not over, Machine learning is still a growing field, and the number of real-world applications will continue to grow. Surrounded by many financial incentives, Machine learning will continue to grow and reshape industries from personalized healthcare treatments, autonomous transportation to more advanced AI-driven customer service and sustainable energy management.
SEO Strategist at Tripadvisor, ex- Seek (Melbourne, Australia). Specialized in technical SEO. Writer in Python, Information Retrieval, SEO and machine learning. Guest author at SearchEngineJournal, SearchEngineLand and OnCrawl.