In the previous article, we discussed the 10 best free, open-source libraries that can be used for categorizing text, which you can find here . But that is an ideal case when you’re neck-deep into coding and machine learning and have the time to spend hours investing in development. So if you’d prefer to get started with a more generic framework, without really getting under the hood, this is the article for you. In this article, we will breakdown the 10 best MaaS/SaaS (Machine Learning as a Service) APIs that can help along your data journey and provide valuable insights without you breaking your head for hours learning about coding. Using ready-to-access solutions, without any prior setup, SaaS/MaaS platforms can help you do complex tasks in machine learning and NLP without being an expert. Thus, your job gets a lot easier without any prior knowledge about the technicality, faster, and more efficiently helping bootstrap your business journey. With NLP models that have been pre-trained to be used without any coding knowledge, MaaS tools have way lot to offer.
Now that we know the basics of how a MaaS platform can help businesses that are looking for a fast and effective use in machine learning, let’s tune in to our top 10 best MaaS APIs for Text Classification.
The Top 10 best NLP Tools
- Google Cloud NLP
- Amazon Comprehend AWS
- IBM Watson
- Microsoft Azure
- MonkeyLearn
- Lexalytics
- MeaningCloud
- Aylien
- ParallelDots
- SummarizeBot
1. Google Cloud NLP
The Google Cloud NLP is a set of machine learning algorithms which can be used for a broader purpose text analytics including text classification, sentiment analysis, entity extraction and an effective ecosystem which provides several ways to build your own pre-trained models. With tools like AutoMl, you can build your own custom ml algorithms and models.
It makes use of Google language/question-answering technology to interpret the right meaning.
Pricing: They provide a free plan, monthly prices can vary according to monthly requests.
2. Amazon Comprehend
Amazon Comprehend AWS is an NLP-based MaaS provider which has been integrated using the web services models from Amazon. It has been trained to do deep learning and NLP analysis like topic modeling, named entity recognition, sentiment analysis, and more. Their interface is integrated for analyzing data from departments like healthcare using Machine Learning algorithms like the Amazon Comprehend Medical.
Pricing: Starts at a free plan, monthly prices can vary according to monthly requests.
IBM Watson is one of the tech giants that provide MaaS technologies which are famous for their suite of ML and AI services that are stored in the IBM cloud. Their key features include Natural Language Processing (NLP), named entity recognition, keyword extraction, sentiment analysis, and much more. Its AI algorithm is tuned to different sectors including healthcare and finance and has a lot of services to get you started on the right path.
Pricing: Starts at a free plan, monthly prices can vary according to monthly requests.
Microsoft Azure is a SaaS-/PaaS-based cloud computing service from Microsoft which can deploy, build and manage apps and services using Microsoft data centres. It supports a wide range of tools, frameworks and programming languages including third party softwares. You can perform NLP tasks without any machine learning expertise, identify key phrases and entities, classify medical terminologies using pre-trained models and perform sentiment analysis over user text in various different languages.
In Microsoft Azure, the following services/toolkits can be used for performing Natural Language Processing activities:
- Azure HDInsight
- Azure Databricks
- Microsoft Cognitive Services
Pricing: Starts at a free plan, monthly prices can vary according to monthly requests.
MonkeyLearn is a SaaS machine learning platform that can build and deploy ready-to-use ML algorithms without any prior knowledge about coding. It offers various NLP tools and services which can be used for classifying text using pre-trained NLP models. It can analyze text data in various formats such as emails, surveys, support tickets, reviews, NPS feedback and social media either from Excel/CSV file or via direct integrations. You can also build custom classifiers to determine the sentiment, topic or intent from the text data or tag the text data using text analysis models.
Pricing: You can try their free plan
Team Plan: $299 per month
Lexalytics is an all-in-one SaaS machine learning platform, which is based on Natural Language Processing (NLP) featuring various solutions for analyzing text. Their Semantria API can analyze hundreds of documents using machine learning algorithms. They offer highly customizable tools for named entity extraction and text categorization which can be tweaked and tailored with the help of their industry standard vocabulary database and the different language support they offer.
Pricing: You can request a demo.
Premium plans depend on the module type and the number of queries per month.
MeaningCloud is a semantic analysis platform that provides ready to access high-end text analysis for businesses. They provide several APIs as predefined categories which can do text classification, text clustering, topics extraction, sentiment analysis, document structure analysis and other such NLP tasks. Their API offers predefined and custom classification models and offers text classification in the form of text from different web pages and social media content in different languages. In general, their tools for multi-tag classification provide several ways for categorizing user text data in a streamlined manner.
Pricing: Has a free plan.
Paid plan: $99 per month.
Aylien is a SaaS API that is based on AI offering various solutions for collecting, analyzing and understanding user text. You can build and train custom NLP models in the cloud based on your own data, collaborate on datasets and models in the Aylien marketplace and much more without any prior knowledge about machine learning, NLP or coding.
Pricing: 14 Day-Trial available
Premium: 199$ per month
ParallelDots is another great cloud NLP API. It consists of document classification and NLP models that are trained to work with thousands of documents accurately and provides real-time sentiment analysis and emotion detection. With an API that is accurate in using insights from open-ended textual data, ParallelDots can work on a variety of data from finance to healthcare and supports flexible deployments via docker containers ensuring there is no data leakage.
Pricing: You can apply for a free trial at their website
SummarizeBot is another great platform which specializes in information extraction, structuring and analysis using AI, nlp, blockchain and machine learning. It offers various products and APIs for summarization, sentiment analysis, emotions/mood analysis, semantic search, named entity detection, intent analysis, keywords extraction and much more.
Pricing: They provide a free 14-days trial
Standard version starts at $179 per month.
Conclusion
With the availability of so many different tools and services, it might get a little hefty to choose the right one for your business. Thus, if you are looking for a tool which is more cost-effective, then MeaningCloud, SummarizeBot and ParallelDots would be an ideal fit! Other than that, if you are looking for a more all-round solution for things like classification, regression, clustering, anomaly detection, recommendation, ranking, etc, then Microsoft Azure would be an ideal fit because of the range of features that it provides excel every other MaaS tool. If you are looking for compatibility with various frameworks/libraries like TensorFlow, Spark MLib, scikit-learn, PyTorch, etc, then IBM Watson will be an ideal fit. If you are looking for a dynamic speech and text processing API, then Google Cloud NLP or Microsoft Azure can be an ideal fit with over 120 plus languages.
References
https://aws.amazon.com/comprehend/
https://cloud.google.com/natural-language
https://monkeylearn.com/blog/text-classification-apis/#google
https://azure.microsoft.com/en-us/
