Foreign Detection Feature Developers Can Now Use Our SDKS or Topic Detection API to Analyze Conversations Based on Discussed Topics

Foreign detection feature developers can now use our sdks or topic detection API to analyze conversations based on discussed topics. This is exciting news for those looking to improve their language processing capabilities, as we are expanding the functionality of our platform to include a new feature that allows users to identify and categorize topics in real-time.

To get started with this new feature, you can make a call to our endpoint at API dot deep ground dot slash V1. Once there, simply enable the topic detection by providing detect topics equal to two as a query parameter. You can use any of the available best client tool out there or also make the call to API programmatically. For this article, we'll be using Postman, but you can choose whatever method works best for your needs.

For our example, let's take a simple file that talks about solar power and renewable energy. After making the API call, you can see that the output includes content topics, which is the section of text where the model has identified topics. You'll also find a list of topics with their Confidence Code. This feature allows you to not only identify what's being discussed but also get a sense of how confident the model is in its categorization.

One of the most impressive aspects of our topic detection feature is that it can identify 350 topics across 10 to 15 categories. This is made possible by unsupervised mod topic modeling techniques, which enable us to automatically recognize patterns and relationships in language data. Not only does this make the feature incredibly powerful, but it also opens up new possibilities for applications such as customer service chatbots, sentiment analysis tools, and more.

In addition to its broad capabilities, our topic detection feature is also versatile enough to work with both English and pre-recorded audio. This makes it an excellent choice for developers working on projects that involve natural language processing or speech recognition.

So how do you get started? First, you'll need to obtain your API keys from our console. These keys will allow you to access the full range of features we offer, including topic detection. Once you have your API keys in hand, you can simply provide them as part of your request when making a call to our endpoint.

To enable topic detection, you'll also need to set detect topics equal to two as one of your parameters. This is where things get really interesting, as this feature allows us to analyze conversations based on discussed topics and identify patterns that may not be immediately apparent.

For our example, we used the Python SDK to make a sample application work. We ran the code, which provided the same output as when we made the call programmatically. This included getting the block of specs for which the model has identified topics and the list of topics with their Confidence Code. As you can see, this feature is incredibly powerful and can help take your language processing projects to the next level.

In conclusion, our topic detection feature is a game-changer for developers working in the field of natural language processing. With its ability to identify 350 topics across 10 to 15 categories, it's clear that we're pushing the boundaries of what's possible with language data analysis. To learn more about this feature and how you can use it in your own projects, be sure to check out our API documentation or visit topic detection.com for more information. Thank you for listening!

"WEBVTTKind: captionsLanguage: enforeign detection feature developers can now use our sdks or topic detection API to analyze conversations based on discussed topics now let me show you how it works you can make a call to our endpoint at API dot deep ground dot slash V1 and simply enable the topic detection by providing detect topics equal to two as a query parameter in my example I'm using Postman but you can use any of the available best client tool out there or you can also make the call to API programmatically uh I have used a very simple file that talks about solar power and renewable energy and after once I've executed the API call you can see that the output blocks content topics uh section of text for which model has identified topics list of topics with their Confidence Code as I mentioned you can also use our sdks to leverage topic detection or call topic detection within the workflow of your own applications you will need to provide your API keys that you can get from our console and to enable the topic detection you will need to provide the detect topics and set it to true as the as one of the parameters I'm using python SDK for my sample application once I run this it provides the same output where it gets the block of specs for which to model has identified topics and list of topics with The Confidence Code now what's messed up about our topic detection feature is that it can identify our 350 topics across 10 to 15 categories it's based on unsupervised mod topic modeling techniques and you can use it for English and pre-recorded audio you can learn more about topic detection.com or on our API documentation thank you for listeningforeign detection feature developers can now use our sdks or topic detection API to analyze conversations based on discussed topics now let me show you how it works you can make a call to our endpoint at API dot deep ground dot slash V1 and simply enable the topic detection by providing detect topics equal to two as a query parameter in my example I'm using Postman but you can use any of the available best client tool out there or you can also make the call to API programmatically uh I have used a very simple file that talks about solar power and renewable energy and after once I've executed the API call you can see that the output blocks content topics uh section of text for which model has identified topics list of topics with their Confidence Code as I mentioned you can also use our sdks to leverage topic detection or call topic detection within the workflow of your own applications you will need to provide your API keys that you can get from our console and to enable the topic detection you will need to provide the detect topics and set it to true as the as one of the parameters I'm using python SDK for my sample application once I run this it provides the same output where it gets the block of specs for which to model has identified topics and list of topics with The Confidence Code now what's messed up about our topic detection feature is that it can identify our 350 topics across 10 to 15 categories it's based on unsupervised mod topic modeling techniques and you can use it for English and pre-recorded audio you can learn more about topic detection.com or on our API documentation thank you for listeningforeign detection feature developers can now use our sdks or topic detection API to analyze conversations based on discussed topics now let me show you how it works you can make a call to our endpoint at API dot deep ground dot slash V1 and simply enable the topic detection by providing detect topics equal to two as a query parameter in my example I'm using Postman but you can use any of the available best client tool out there or you can also make the call to API programmatically uh I have used a very simple file that talks about solar power and renewable energy and after once I've executed the API call you can see that the output blocks content topics uh section of text for which model has identified topics list of topics with their Confidence Code as I mentioned you can also use our sdks to leverage topic detection or call topic detection within the workflow of your own applications you will need to provide your API keys that you can get from our console and to enable the topic detection you will need to provide the detect topics and set it to true as the as one of the parameters I'm using python SDK for my sample application once I run this it provides the same output where it gets the block of specs for which to model has identified topics and list of topics with The Confidence Code now what's messed up about our topic detection feature is that it can identify our 350 topics across 10 to 15 categories it's based on unsupervised mod topic modeling techniques and you can use it for English and pre-recorded audio you can learn more about topic detection.com or on our API documentation thank you for listening\n"