Are you using Aylien but aren’t entirely satisfied with how it functions? Then keep reading to learn about 3 API alternatives that will enable you to receive excellent text categorization results!
When working on a supervised machine learning problem using a particular data set, you experiment with different methods and strategies to find models that generate general hypotheses, which subsequently allow for the most accurate predictions about future instances, conceivable.
The same concepts apply to classifying texts (or documents): a text classifier can be trained using a variety of models. Which machine learning model is the best? is always answered with “it depends.” The performance of an algorithm cannot be predicted by even the most seasoned data scientists without first being tested.
A business intelligence tool called AYLIEN uses text analytics to glean information from news articles. The platform can be used for risk intelligence, media intelligence, product development, and other things in the financial services, information services, and media monitoring industries.
Topic, category, and entity labeling are added to the data using natural language processing (NLP), and events are identified and clustered for more in-depth discovery and analysis. At the level of the entity, sentence, and entire piece, sentiments are classified as positive, negative, and neutral.
Let us show you 3 more alternatives to Aylien.
Klazify
The APIs and data feeds provided by Klazify are used by network and cybersecurity businesses all over the world to give industry-leading risk information and domain categorizations. For instance, one can learn more about network traffic or categorize user access records using the domain classification API offered by Klazify. Klazify leverages 66 separate data feeds to complement the engine.
Using Klazify’s Website Categorization API, a machine learning (ML) engine scans the content and meta tags of a website. It extracts text from the webpage and classifies it into up to three categories using natural language processing (NLP).
Nyckel
This quick and secure API makes it possible to fully automate the integration of THEIR Machine Learning service into your application. Your own hosted machine learning model can be trained in a matter of minutes. The model can be deployed instantly and then immediately integrated into your application.
Data annotating, reviewing, and mining are all seamlessly integrated into your ML process by Nyckel UI. Additionally, by using fully automated and highly parallelized AutoML, leading deep learning approaches are taught and evaluated on your data in a matter of seconds.
Get all its data here https://www.nyckel.com/
MeaningCloud Text Classification API
Text Classification is the name of MeaningCloud’s automatic document classification service. Using either user-defined or widely used domain-specific taxonomies, it divides texts into one or more groups (like IPTC, IAB, and ICD-10) The method achieves high levels of accuracy and flexibility in a number of scenarios by combining statistical document classification with rule-based filtering.
The use of document examples to define each category is provided by statistical classifiers. Rule basis classifiers can then be used to enhance and rectify the output of statistical classifiers.
Go to https://www.meaningcloud.com/developer/text-classification to find more about it