Waydev
GitPrime
LinearB
Haystack Analytics
CodeClimate
Code Climate Velocity
GitClear
Teamplify
TensorFlow
PyTorch
Keras
Scikit-learn
OpenCV
IBM Watson Studio
Amazon SageMaker
Pega Platform
Waydev helps managers to move from a feeling driven to a data-driven approach. Waydev includes concrete metrics for your daily stand-ups, 1-to-1 meetings, checking the history of the engineers work and benchmarking your stats with the industry.
Waydev TensorFlowBased on our record, TensorFlow should be more popular than Waydev. It has been mentiond 7 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.
For example, in our traditional approach, every step and process is defined and has to be adhered to. Any change has to go through multiple approvals. The scope in itself has a very limited scope or flexibility towards change. I am on the fence looking for resources and tools that will help to slowly execute and implement these changes. With regards to resources, I am currently looking at the scrum guide and with... Source: almost 2 years ago
When you’re ready to translate data into greater visibility, and this visibility into faster, more efficient teams, you can start looking at development analytics platforms like Waydev. - Source: dev.to / over 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
GitPrime - GitPrime uses data from any Git based code repository to give management the software engineering metrics needed to move faster and optimize work patterns.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
LinearB - LinearB delivers software leaders the insights they need to make their engineering teams better through a real-time SaaS platform. Visibility into key metrics paired with automated improvement actions enables software leaders to deliver more.
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
Haystack Analytics - Ship faster and improve team satisfaction with engineering analytics powered by your Github data.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
