Disadvantages are present in every tool for editing every file type, and even though you can find many tools out there, not all of them will fit your particular requirements. DocHub makes it much simpler than ever to make and change, and handle papers - and not just in PDF format.
Every time you need to quickly strike out light in xml, DocHub has got you covered. You can effortlessly alter document elements including text and pictures, and structure. Customize, arrange, and encrypt paperwork, create eSignature workflows, make fillable documents for stress-free data gathering, etc. Our templates feature allows you to generate templates based on papers with which you often work.
In addition, you can stay connected to your go-to productivity capabilities and CRM platforms while handling your paperwork.
One of the most extraordinary things about utilizing DocHub is the option to deal with document activities of any complexity, regardless of whether you need a fast tweak or more complex editing. It comes with an all-in-one document editor, website form builder, and workflow-centered capabilities. In addition, you can be certain that your papers will be legally binding and comply with all security protocols.
Cut some time off your projects with DocHub's tools that make handling paperwork effortless.
so we will begin with a quick uh introduction of the domain which is Extreme multilevel classification so extreme classification also known as XML is a rapidly growing research area in machine learning that deals with multi-b problems which involves a large number of labels these uh these the number of labels in these problems are uh can go up to billions and uh this this has a large uh lot of applications in various Fields like NLP computer vision and bioinformatics most importantly it is being used as a new approach for industrial applications like ranking and recommendation uh where it provides ad advantages over uh the traditional methods uh several search engines like Bing have used uh XML in their ad recommended systems as well as Amazon has uh used it for uh for Doc for object tagging and and several other applications so why machine learning is different from other uh other domains is uh is due to these reasons the first is that the number of labels uh uh is very large
