As a well known fact, for machine learning, an artificial intelligence (AI) GPU or graphical processing unit does matter to accelerate at least 5x for whatever tasks involved. It is due to the fact that there are a lot of execution units (or cores) involved. However for the coming new CPU, it may not be
Today we continue Machine Learning domain post, focus on Benefits of Transfer Learning to Deep Learning. Transfer Learning (TL) for Deep Learning (DL) is a machine learning (ML) approach and techniques used to save time and resources from having to train multiple machine learning models from scratch to complete similar tasks, in particular for tasks
The term ML isn’t new, it was invented in 1959. Machine learning enables the computers with the right software application to learn from the historical data and formulate a solution which can be used to solve similar problems in future, without the explicit need of further instruction by humans to inform computers of all the combinations of
Model Operations (ModelOps) is to focus primarily on the governance and life cycle management of a wide range of operationalized AI (Artificial Intelligence) and decision models. This includes knowledge graphs, optimization, rules, machine learning, agent-based models, and linguistics. Model Operations (ModelOps) is at the center of every organization’s enterprise AI approach, if you are yet
Recently, many organizations and enterprises had realized the benefit of adapting composite AI over machine learning in managing data analysis. Previously, machine learning which is a method of data analysis that automates analytical model building a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions
Hyperautomation has goes beyond our typical automation technology. In simple words, hyperautomation makes use of the bot’s intelligence by creating a union of different automation, all of which complement each other for a smarter outcome. Upgrading robotic processes with intelligence, creates an intelligent digital workforce that can reduce the human burden. With technology and humans
The enthusiasm for Machine Learning (ML) can be appreciated by essentially understanding that there is a development in volumes and varieties of raw data, the various procedures, and hence, there is a need to find affordable data storage. The need of the hour is to implement a method by which organizations can quickly and automatically
Transfer learning is a research problem in machine learning that focuses on storing knowledge gained while solving one problem and applying it to a different but related problem. This post focuses on discussing the theory of transfer learning, under Deep Learning (DL) in Machine Learning (ML) context from the educational aspect. The first theory of transfer
A Continuous Intelligence (CI) framework starts with the process of acquiring data and, with the help of analytics and machine learning (ML), derive insights from it to be able to make confident decisions and actions which are in turn reviewed and validated, to ensure the organisation continuously improves its decision-making capabilities, for decision support. Building