The technique of scaling generates infinite values on the objects to be measured. These techniques help understand the relationship between the objects. Let us see the techniques − Comparative scales It is the direct comparison of objects. The types include − Rank Order Constant sum scaling Rank order One item is judged against the rest of the objects. The respondents contain several objects who rank/order the objects based on a criteria. Rank order scaling is ordinal in nature, that is, (n-1) scaling decisions are made in this technique. Constant sum scaling In this technique, a constant sum of ... Read More

The field of machine learning is developing rapidly, and the benefits are innumerable. Some of the benefits in the field of business have been listed below − Improved Consumer Experience Human efforts to interact with consumers have reduced and bots are used instead. This has helped with the automated and travail responses that are required at times. Human resources can be used for better tasks as well. Resource Planning Since patterns can be detected from data, the resources required can be planned, and can be utilised efficiently. This way, machine learning makes businesses cost effective too. Effective Predictions Predictions based ... Read More

Knowledge-based agents represent searchable knowledge that can be reasoned. These agents maintain an internal state of knowledge, take decisions regarding it, update the data, and perform actions on this data based on the decision. Basically, they are intelligent and respond to stimuli like how humans react to different situations. Examples − Based on the user's question (that behaves as the external stimuli), they provide an answer from their knowledge base (the data warehouse where they store basic knowledge) that provides a satisfactory answer to the user’s question. Knowledge Base Features It has the below-mentioned features − Knowledge base (KB) It is ... Read More

Artificial intelligence deals with programming computers to detect patterns in new data, make decisions based on user input, and give output based on the user input. All the rules are not explicitly defined and it is expected by the developer that the machine learns these rules by experience, using a reward-punishment mechanism. Applications of Machine Learning Artificial intelligence has come a long way with self-driving cars, bots, object and facial recognition, and much more. In recent times, algorithms have been developed with a better accuracy that can help provide outputs which have better accuracies. Due to the improvements in ... Read More

What is MLOps? Machine Learning Operations (MLOps) is an acronym for Machine Learning Operations. MLOps is a basic component of Machine Learning engineering that focuses on optimizing the process of deploying machine learning models and maintaining and monitoring them. MLOps is a team effort that frequently includes data scientists, DevOps engineers, and IT. MLOps aims to boost automation and improve the quality of production models while simultaneously concentrating on business and regulatory needs, similar to DevOps and DataOps methodologies. MLOps began as a set of best practices, but it is gradually becoming a stand-alone solution to managing the ML lifecycle. ... Read More

It would have often occurred that the development team has moved on to a new project while the operations team provides feedback on the previous one. This caused the deadline to be pushed back, for the entire software development cycle or machine learning model development cycle. For this reason, IT has adopted the new ways of working for preparing software and machine learning models, they are MLOps and DevOps. In this blog, you will get to know about these terms and how they differ. What is DevOps? The term DevOps stands for Development + OperationS. It is a method in ... Read More

In the IT industry, each of these operational domains is cross-functional and provides a distinct value. And each of the Ops domains stems from a common broad mechanism of agile concepts, which were originally initially developed for the guidance of software developers for their development, but now have spread its wings to other domains of related technologies that are data-driven applications, AI, and ML. In this post, you will come across the popular terms in the world of Artificial Intelligence that have emerged to great extent. What is MLOps? MLOps is a collaboration and communication platform for data scientists and ... Read More

MLOps (Machine Learning Operations) has become a trend in the current world of Artificial Intelligence. There are several operations that are part of any machine learning process. This includes data versioning, feature engineering, model monitoring, experiment tracking, model serving, model deployment, etc. There are several tools and platforms in the market that could help you with these processes and get your work done efficiently with proper risk analysis. However, before you choose a product or platform for your project, you should thoroughly research it. Furthermore, you must ensure that the tools are compatible with the rest of your stack. So, ... Read More

A collection of methods, tools, and approaches are considered for a machine learning project to be successful and MLOps is a wide phrase that encompasses these approaches. Machine Learning Operations (MLOps) is a set of methods where data scientists and operations experts come together to collaborate and communicate. It's a machine-learning version of DevOps that's been tweaked to meet various ML components, such as changing data and the addition of new development jobs, such as ML engineers and data scientists. It's gradually becoming a stand-alone method for ML lifecycle management. Data collection, model generation, continuous integration/continuous delivery, orchestration, deployment, diagnostics, ... Read More

Algorithms are ubiquitous, and a good number of us make use of them, although we may not even be aware that one is involved in the process. We require an algorithm to use a computer to solve a problem. When it comes to transforming datasets into models, machine learning relies on a number of different techniques.Both bias and variance are essential components to understand when working with machine learning. When it comes to achieving high levels of accuracy in any machine learning algorithm, having a solid understanding of each of these concepts is essential.What is Bias in Machine Learning?Every machine ... Read More