Based on our record, DuckDB should be more popular than TensorFlow. It has been mentiond 15 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.
I have lived through the hype of Big data it was a time of HDFS+HTable I guess and Hapoop etc. One can't go wrong with DuckDB+SQLite+Open/Elasticsearch either with 6 to 8 even 10 TB of data. [0]. https://duckdb.org/. - Source: Hacker News / 19 days ago
More than once, I have been in a situation where I needed to query CloudTrail logs but was working in a customer environment where they weren’t aggregated to a search interface. Another similar situation is when CloudTrail data events are disabled for cost reasons but need to be temporarily turned on for troubleshooting/audit purposes. While the CloudTrail console offers some (very) limited lookups (for management... - Source: dev.to / 26 days ago
DuckDB: An in-process SQL OLAP database management system. While not a traditional OLAP database, DuckDB is designed to execute analytical queries efficiently, making it suitable for analytical workloads within data-intensive applications. - Source: dev.to / 4 months ago
Easiest way to practically use SIMD table scan database is try out DuckDB: https://duckdb.org/. - Source: Hacker News / 4 months ago
Duckdb so we can make OLAP like queries on the data. - Source: dev.to / 6 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 1 year 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: almost 2 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 2 years ago
I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org. Source: about 2 years ago
I have looked at this TensorFlow website and TensorFlow.org and some of the examples are written by others, and it seems that I am stuck in RNNs. What is the best way to install TensorFlow, to follow the documentation and learn the methods in RNNs in Python? Is there a good tutorial/resource? Source: about 2 years ago
Apache Druid - Fast column-oriented distributed data store
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
OctoSQL - OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL. - cube2222/octosql
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
MonetDB - Column-store database
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.