No features have been listed yet.
No Flagsmith videos yet. You could help us improve this page by suggesting one.
Based on our record, Flagsmith should be more popular than TensorFlow. It has been mentiond 13 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.
Considering all these points, the team at Flagsmith has developed a feature flag management platform Flagsmith and made it open source. The core functionality is open and you can check out the GitHub repository here. I have utilized and authored several blogs discussing their excellent offerings and strategies. - Source: dev.to / 2 months ago
Flagsmith - Release features with confidence; manage feature flags across web, mobile, and server side applications. Use our hosted API, deploy to your own private cloud, or run on-premise. - Source: dev.to / over 1 year ago
Flagsmith is written in Django and is open source as well: https://flagsmith.com. Source: almost 2 years ago
Before we dive in, one important call-out: We provide our feature management product to customers in three ways depending on how they want to have it managed: Fully Managed SaaS API, Fully Managed Private Cloud SaaS API and Self-Hosted. The infrastructure costs that we are sharing is for our customers that leverage our Fully Managed SaaS API offering (try it free: https://flagsmith.com/) which represents a portion... - Source: dev.to / about 2 years ago
On March 15th, Sebastian Rindom, the CEO & Co-founder of Medusa, did an interview with Flagsmith where he talked about how Medusa started, why create a headless commerce solution, why make it open-source, and more. - Source: dev.to / about 2 years 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
LaunchDarkly - LaunchDarkly is a powerful development tool which allows software developers to roll out updates and new features.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
ConfigCat - ConfigCat is a developer-centric feature flag service with unlimited team size, awesome support, and a reasonable price tag.
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
Unleash - Open source Feature toggle/flag service. Helps developers decrease their time-to-market and to increase learning through experimentation.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.