Metaplane
Masthead Data
Baresquare
DQOps
IntelliFront BI
DQLabs.ai
Percival
Keyboard Pilot
TensorFlow
PyTorch
Keras
IBM Watson Studio
Scikit-learn
Azure Machine Learning Service
Pega Platform
Azure Machine Learning Studio
Data teams are often the last to know about data quality issues, finding out only when downstream data consumers complain about broken dashboards. Metaplane solves this problem by continuously monitoring the entire data stack, alerting teams when something goes wrong, and providing context about what caused the issue.
Metaplane is the only data observability tool that is free to try and can be setup in under 10 minutes. After connecting your warehouse, our test engine automatically adds thousands of tests for row counts, freshness, and statistical properties, all without writing a single line of code.
Using your query history, transformation tool and BI tools, Metaplane can construct lineage across your entire data stack. When an issue is spotted, Metaplane will send you an alert to Slack or email and provide context about what may have caused the issue as well as what could be impacted.
Metaplane TensorFlowBased on our record, TensorFlow should be more popular than Metaplane. It has been mentiond 8 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.
After evaluating few solutions in the market: We were in the market to hunt for a solution which will cost under 10k (yearly) considering the cost of opensource will be similar considering DE resource and maintenance cost etc 1. MonteCarlo - Super duper expensive - Unable to hosting in Google Cloud 2. BigEye - Good features 3. Metaplane - Overall good package but when compared to catalog and other features it... Source: over 3 years ago
The open-source movement offers hope here. Projects like Hugging Face are democratizing access to state-of-the-art models, while initiatives like Google's TensorFlow provide powerful frameworks without licensing costs. But even open-source solutions require technical expertise that many lack. - Source: dev.to / 4 months ago
Converting the images to a tensor: Deep learning models work with tensors, so the images should be converted to tensors. This can be done using the to_tensor function from the PyTorch library or convert_to_tensor from the Tensorflow library. - Source: dev.to / over 3 years ago
So I went to tensorflow.org to find some function that can generate a CSR representation of a matrix, and I found this function https://www.tensorflow.org/api_docs/python/tf/raw_ops/DenseToCSRSparseMatrix. Source: about 4 years ago
Can anyone offer up an explanation for why there is a performance difference, and if possible, what could be done to fix it. I'm using the installation guidelines found on tensorflow.org and installing tf2.7 through pip using an anaconda3 env. Source: about 4 years ago
I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org. Source: over 4 years ago
Masthead Data - Masthead Data helps data teams to identify and fix data errors before they become a problem for data consumers. It catches anomalies in the data warehouse in real time.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Baresquare - Get daily business insights and actions served up with your morning coffee using Baresquareโs scalable AI-powered analytics platform.
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
DQOps - Increase confidence in your data by tracking the data quality
IBM Watson Studio - Learn more about Watson Studio. Increase productivity by giving your team a single environment to work with the best of open source and IBM software, to build and deploy an AI solution.