Application of ELM

Extreme learning machine is used in wide range of application in machine learning and artificial intelligence which are listed below,

1. It is used in Image recognition and classification task, where applied to identify object in photos and perform analysis on medical image reports.
2. ELM is used in Speech recognition task, by converting human speech to text which applied in voice assistants, transcription services.
3. It is used in various Natural language processing tasks, including text classification, sentiment analysis, language translation, and chatbot development.
4. ELM is used in finance sector to predict stock prices, exchange rates, and other financial data which beneficial for trader and investors.
5. It is used in social media analysis by implementing sentiment analysis, trend detection, and user behavior understanding, which is beneficial for marketing and brand management.
6. It is used in recommendation system that suggest products, content, or services to users based on their preferences and behavior which is beneficial to e-commerce website and content platform.
7. It is used for predictive maintenance, helping to prevent equipment failures by analyzing sensor data which is beneficial to manufacturing industries.

Extreme Learning Machine commonly referred to as ELM, is one of the machine learning algorithms introduced by Huang et al in 2006. This algorithm has gained widespread recognition in recent years, primarily due to its lightning-fast learning capabilities, exceptional generalization performance, and ease of implementation. This makes it awesome for businesses and researchers because they can get results fast and efficient way. It provides a significant contribution to fields like Image recognition, speech recognition, Natural language processing financial forecasting, medical diagnosis, social media analysis, and recommendation systems.

In this article, we will dive deep into the concept of an “Extreme learning machine” by explaining its architecture, training process, and application which are listed below in the table of contents.