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APILayer’s 7 AI & Machine Learning APIs for Python Developers

Python is great for AI and Machine Learning. Working with AI and ML libraries, however, sometimes can be a challenge. 

That’s why APILayer, which belongs to the Idera family like Embarcadero, has no less than seven APIs designed to make your life easier as you deploy AI and ML in your software.

These APIs come with simple and easy-to-apply Python documentation, and even junior Python developers in your team can implement these API solutions into your business processes and automation.

Which Python Libraries Are Used For Machine Learning? What Do They Do?

Some of the most popular Python libraries for Machine Learning are scikit-learn, TensorFlow, and Keras. These libraries provide tools that can be used to build, train, evaluate and optimize Machine Learning models.

So What Are AI & Machine Learning APIs?

AI & Machine Learning APIs are web-based services that provide access to AI & Machine Learning models. These APIs can be used to develop new applications or improve the performance of existing applications.

Why Use a Machine Learning API Rather Than a Machine Learning Python Library?

You might want to use a Machine Learning API rather than a Machine Learning Python library for three key reason reasons:

How Can I Use APILayer’s AI & Machine Learning APIs?

You can use AI & Machine Learning APIs by making calls to the API using a programming language like Python or Java. These calls will allow you to access the API’s AI & Machine Learning models. To make an API call, you will need to have the API URL, the name of the API method you wish to call, any parameters that the method requires, and your API key. The methods and parameters will depend on the API you are using. If you use the Python requests library, the results from the URL will be returned in JSON format.

APILayer’s AI & Machine Learning APIs

APILayer offers a number of different AI and Machine Learning APIs that can help you with everything from natural language processing to predictive modeling.

In this blog post we will look at the following seven:

1. Natural Language Processing API

The APILayer NLP API is one of the best ways to get started with natural language processing in Python. 

The NLP API can extract meaning from text and make your applications more intelligent. It API can help you with tasks such as sentiment analysis, text classification, entity extraction, and more. It also offers NLP features that include part-of-speech tagging, named entity recognition, and sentiment analysis.

Consider combining this API with Python’s Beautiful Soup Library to analyze and tag data found on websites, or Python libraries used for reading word documents to analyze text in documents.

Explore the documentation and get yourself a FREE API key

2. Sentiment API

APILayer’s Sentiment API uses natural language processing to determine the sentiment of a piece of text. It can be used to analyze social media data, customer reviews, or any other type of text data. The API is easy to use, and it offers a free plan with up to 300 requests per month.

Features include sentiment analysis of customer reviews, automated customer support, text classification, language detection, summarization, and chatbots

Explore the documentation and get yourself a FREE API key

3. “Did you mean this” API

Google’s famed “Did you mean this?” feature is a powerful feature to easily guide your users for corrections. The Did You Mean This API features a fast and convenient way to embed this feature into your application. 

Business use cases include: 

View the documentation and get yourself a FREE API key:

4. Keyword API

With APILayer’s Keyword API, you can extract the most relevant words and expressions from text. Keyword extraction helps you find out what’s relevant in a sea of unstructured data. Extract keywords or key phrases to discover the main topics in your text. 

Business use cases include: 

Check out the documentation on the link below and get yourself a FREE API key.

5. Text to Emotion API

If you’re looking for a way to add emotional context to your text data, the APILayer Text to Emotion API is worth exploring. This API uses natural language processing to analyze text and return a score for six different emotions: anger, fear, joy, sadness, disgust, and surprise. You can use this API to analyze social media posts, customer feedback, or any other text data that you have.

Check out the documentation on the link below and get yourself a FREE API key

6. Bad Words API

If you are looking for a way to filter out bad words from your text, then the Bad Words API from APILayer is an excellent option. This API allows you to quickly and easily filter out bad words from your text and is straightforward. Send a request to the API with the text you want to filter, and the API will return a list of bad words found in the text.

Check out the documentation on the link below and get yourself a FREE API key.

7. Resume Parser API

The APILayer Resume Parser API allows you to parse resumes and extract data such as contact information, education and work history, skills, and more. This can be useful for building a database of candidates for a job or for creating a profile of an individual for research purposes. The APILayer resume parser API is easy to use and provides good results.

This API would be beneficial for you if you are developing any of the following business ideas:

Check out the documentation on the link below and get yourself a FREE API key.

Talk to Us!

There it is, our list of seven great APIs by APILayer. Need help deciding which are best for your business? Talk to us! We’re here to help you achieve your goals.

Contact us today to get started.

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