As edge devices gain greater computing power and machine learning becomes more mature, it becomes possible to infuse intelligence into edge devices. This article explores the impact that AI and ML will have on edge computing.

Enterprises nowadays are increasingly utilizing machine learning for acquiring, storing, and analyzing data in order

In the modern business landscape, most enterprises depend on machine learning (ML) applications to understand potential sources of revenue, recognize market trends, anticipate customer behavior, forecast pricing fluctuations, and ultimately, make informed business decisions. The development of these ML applications necessitates meticulous planning and a structured approach. The major steps in this process include defining the problem, cleaning, and preparing the data, engaging in feature engineering, conducting model training, and continually refining the model’s accuracy.

While the earlier decade was all about data communication and internet proliferation, the economy of

The recent advancement in artificial intelligence and machine learning has contributed to the growth of computer vision and image recognition concepts. From controlling a driver-less car to carrying out face detection for a biometric access, image recognition helps in processing and categorizing objects based on trained algorithms. Keep reading to understand what image recognition is and how it is useful in different industries.

Businesses constantly need to evolve and adopt newer trends to succeed. These days companies are implementing chatbots that help in solving customer queries, improving communication, and remote troubleshooting to enhance customer experience. This article provides a complete guide to chatbot development, including use cases, tools, and best practices to consider while developing chatbots for your business.