Versatile Data Kit
Mage AI
TensorFlow
Meltano
Microsoft Power Automate
Caravel
Apache Spark
Apache Airflow
NumPy
Pandas
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
Figure Eight
Versatile Data KitNo features have been listed yet.
No Versatile Data Kit videos yet. You could help us improve this page by suggesting one.
Based on our record, NumPy seems to be a lot more popular than Versatile Data Kit. While we know about 119 links to NumPy, we've tracked only 10 mentions of Versatile Data Kit. 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.
I work at VMware and we use one tool for the whole ELT, it was made internally as there was no good alternative at the time and now we opensourced it, here it is: https://github.com/vmware/versatile-data-kit. Source: over 2 years ago
"suggestions on how to reduce the time spent on initially generating and adjusting the code" is using some tools that automate ELT. Here's one open-source tool I'm working on with my team: https://github.com/vmware/versatile-data-kit. Source: over 2 years ago
Have you heard about versatile data kit (https://github.com/vmware/versatile-data-kit)? I think it meets your needs perfectly:. Source: over 2 years ago
Versatile Data Kit is a framework to bBuild, run and manage your data pipelines with Python or SQL on any cloud https://github.com/vmware/versatile-data-kit Here's a list of good first issues: https://github.com/vmware/versatile-data-kit/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22 Join our slack channel to connect with our team: https://cloud-native.slack.com/archives/C033PSLKCPR. Source: over 2 years ago
There are some DE tools now that provide automation, so you don't need to have advanced Python to build your pipelines, like this one here: https://github.com/vmware/versatile-data-kit. Source: over 2 years ago
The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 4 months ago
This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 9 months ago
The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 9 months ago
It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 10 months ago
The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 10 months ago
Mage AI - Open-source data pipeline tool for transforming and integrating data.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Meltano - Open source data dashboarding
OpenCV - OpenCV is the world's biggest computer vision library
