Microservices architecture is an increasingly popular approach to AI development, allowing developers to break their applications into smaller services that are easier to manage and update. This architecture offers a range of benefits, including scalability, agility, and improved maintainability.
RPA is a powerful tool for businesses to leverage in order to increase efficiency, reduce costs and streamline operations. RPA is an innovative technology that allows software robots to work with existing systems to automate manual processes while eliminating the need for error-prone manual labor.
Applied artificial intelligence (AI) is revolutionizing the way businesses operate and compete across nearly all industries. The ability of AI to enhance operational efficiencies, automate mundane tasks, and offer deeper insights into customer behavior is undeniable.
Forecasting is a technique used to help make predictions about the future. It can be used to identify potential changes in demand, predict potential opportunities or risks, and plan for upcoming events. Forecasting can help businesses better understand the underlying trends and patterns in their industry, enabling them to make
Machine learning is a field of technology that has the potential to revolutionize many aspects of our lives. Machine learning involves developing algorithms and models that can ‘learn’ from input data and make predictions or decisions without being specifically programmed to do so.
It is important for a small company to differentiate between data scientist and data engineer roles since both roles have separate skill sets and responsibilities throughout an AI project.
Active Learning is a type of machine learning algorithm that actively interacts with its environment to learn from it. It works by selecting the data points that are most useful for training and labeling them, allowing the model to train on fewer labeled data points.
When it comes to the practical implementation of RPA, your company can face many business and technical challenges. That’s why RPA implementation always implies a procuring strategy of automating the processes one by one.
What is the difference between applied research and basic research in AI development? What is the difference between AI strategy and AI execution within a business context? These are questions that many businesses are asking themselves as they begin to invest in artificial intelligence.
Artificial intelligence, or AI, is a term that has been tossed around a lot lately. It seems like every other business is using it in their marketing materials and trying to convince you that they need to use it too. But what is AI, really?
Python has emerged as the leading language for machine learning development for several reasons: its ease of use, wide availability of libraries, and strong community support. In this blog post, we will discuss the benefits of using Python in machine learning projects.
Anomaly detection is the identification of items, events, or observations that do not conform to an expected pattern or other items in a dataset.
There is a lot of confusion surrounding the role of a machine learning engineer and data scientist. Some people think they are one and the same, while others believe they are in completely different positions. So, what is the difference?
Anyone running a business wants to predict its future. Though it is not possible exactly to some extent, you can get an estimation because business comes with uncertainty and risks that can not be avoided but can be minimized using Predictive Forecasting.
Forecasting is the process of predicting future events. This can be done through a variety of methods, but machine learning is becoming increasingly popular for forecasting due to its accuracy and ability to account for changes in data.
What is data augmentation, how does it work, and what are its most prominent use cases? Learn everything you need to know about data augmentation techniques for computer vision and start training your AI models.