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TensorFlow might be a bit more popular than AnalyticsVerse. We know about 7 links to it since March 2021 and only 7 links to AnalyticsVerse. 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.
AnalyticsVerse helps software engineering teams transform their development processes by tracking the right software engineering KPIs. - Source: dev.to / over 1 year ago
Explore how AnalyticsVerse facilitates process improvements and assists 10x tech leads here. - Source: dev.to / over 1 year ago
We initially went with Gitlab due to better CI/CD capabilities(pre-Github Actions) and Jira because AnalyticsVerse integrates with Jira and using it within the team gave us a better understanding of it. - Source: dev.to / almost 2 years ago
Once these decisions are made, any tech lead will keep making smaller reversible decisions every other day with a few occasional big irreversible decisions. Here are some of those big technical decisions that we’ve made at AnalyticsVerse. - Source: dev.to / almost 2 years ago
Yes, I quit my job at Morgan Stanley to start an exciting new journey as one of the co-founding members of AnalyticsVerse! - Source: dev.to / almost 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
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Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
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Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.