Based on our record, TensorFlow should be more popular than Evidently AI. 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.
It is doable. However the main focus of MLFlow is in experiment tracking. I would suggest for you to look into another monitoring tools such evidentlyai . You can track more things than performance (e.g.data drift). Which may be helpful in a production setting. Source: over 1 year ago
Evidently is an open-source Python library that analyzes and monitors machine learning models. It generates interactive reports based on Panda DataFrames and CSV files for troubleshooting models and checking data integrity. These reports show model health, data drift, target drift, data integrity, feature analysis, and performance by segment. - 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 / about 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: almost 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
ML5.js - Friendly machine learning for the web
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
ML Showcase - A curated collection of machine learning projects
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Lobe - Visual tool for building custom deep learning models
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.