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Based on our record, MindsDB should be more popular than Embeddinghub. It has been mentiond 12 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Install MindsDB locally or sign up for the MindsDB Cloud account. - Source: dev.to / about 1 year ago
Step 1: Create a MindsDB Cloud Account, If you already haven't done so. - Source: dev.to / over 1 year ago
You check out MindsDB by signing up for a demo account. If you would like to learn more you can visit MindsDB's Documentation. If you want to contribute to MindsDB, visit their Github repository and if you like it give it a star. MindsDB has a vibrant Slack Community and amazing team that provides technical support, if you would like to join you can sign up here. - Source: dev.to / over 1 year ago
Using Large Language Models in your database can help improve your product by helping you gain insights from data, make relevant predictions, understand user behavior, and generate contextually relevant human-like content. MindsDB allows you to build AI applications fast by simplifying the processes of using ML models inside your database. The models are designed to be production ready by default without the need... - Source: dev.to / over 1 year ago
MindsDB provides all users with a free MindsDB Cloud version that they can access to generate predictions on their database. You can sign up for the free MindsDB Cloud Version by following the setup guide. Verify your email and log into your account and you are ready to go. Once done, you should be seeing a page like this :. - Source: dev.to / about 2 years ago
Featureform The success of a machine learning model relies on the quality of data and, hence, the features fed to the model. However, in large organizations, members of one team may not be aware of good features developed by other teams in the organization. A feature store helps eliminate this problem by providing a central repository of features that are accessible to all the teams and individuals within an... - Source: dev.to / 9 months ago
Featureform is a virtual feature store. It enables data scientists to define, manage, and serve their ML model's features. Featureform sits atop your existing infrastructure and orchestrates it to work like a traditional feature store. By using Featureform, a data science team can solve the organizational problems:. Source: almost 3 years ago
Usually embeddings — dense numerical representations of real-world objects and relationships, expressed as a vector — are stored in database servers such as PostgreSQLEmbedding. However Embeddinghub makes it easier to store your embeddings and load them. You can get started with minimal setup, and it also makes your code look less verbose as compared to, say, building a KNN model using scikit-learn. - Source: dev.to / almost 3 years ago
SuperDuperDB - Say goodbye to complex MLOps pipelines and specialized vector databases. Integrate and train AI directly with your preferred database, only using Python.
Lionbridge - Translation productivity platform
Zetane Systems - Powerful software for AI in business & industry
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StoryboardHero - Drastically reduce time and cost to create storyboard
GiniMachine - Fighting bad loans with AI
