tensor-house VS vectordb-recipes

Compare tensor-house vs vectordb-recipes and see what are their differences.

tensor-house

A collection of reference Jupyter notebooks and demo AI/ML applications for enterprise use cases: marketing, pricing, supply chain, smart manufacturing, and more. (by ikatsov)

vectordb-recipes

High quality resources & applications for LLMs, multi-modal models and VectorDBs (by lancedb)
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SaaSHub helps you find the best software and product alternatives
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tensor-house vectordb-recipes
4 1
1,163 390
- 11.8%
7.5 9.5
3 months ago 5 days ago
Jupyter Notebook Jupyter Notebook
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

tensor-house

Posts with mentions or reviews of tensor-house. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-04-08.

vectordb-recipes

Posts with mentions or reviews of vectordb-recipes. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing tensor-house and vectordb-recipes you can also consider the following projects:

EconML - ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

learnopencv - Learn OpenCV : C++ and Python Examples

Robyn - Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community.

Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.

models - A collection of pre-trained, state-of-the-art models in the ONNX format

clip-retrieval - Easily compute clip embeddings and build a clip retrieval system with them

Workshops - Workshops organized to introduce students to security, AI, blockchain, AR/VR, hardware and software

AI-For-Beginners - 12 Weeks, 24 Lessons, AI for All!

models - Models and examples built with TensorFlow

mta - Multi-Touch Attribution

Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

lolesports-predictor - Personal machine learning & GUI project to predict League of Legends Esports game results between two teams