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Based on our record, Google Cloud Machine Learning should be more popular than TensorFlow. It has been mentiond 21 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.
2. Google Cloud Vertex AI: https://cloud.google.com/vertex-ai. Policy: https://cloud.google.com/vertex-ai/docs/generative-ai/data-governance#foundation_model_training. - Source: Hacker News / 2 months ago
Google Cloud Platform (GCP) provides a very befitting Machine Learning solution called Vertex Ai that handles Google Cloud's unified platform for building, deploying, and managing machine learning (ML) models. Our goal is to build a simple Machine Learning application that optimizes all that GCP provides plus an implementation of continuous integration and continuous development (CI/CD). - Source: dev.to / 4 months ago
Cross posting some links from another post that HNers found helpful - https://cloud.google.com/vertex-ai (marketing page) - https://cloud.google.com/vertex-ai/docs (docs entry point) - https://console.cloud.google.com/vertex-ai (cloud console) - https://console.cloud.google.com/vertex-ai/model-garden (all the models) - https://console.cloud.google.com/vertex-ai/generative (studio / playground) VertexAI is the... - Source: Hacker News / 5 months ago
For the peer comments - https://cloud.google.com/vertex-ai (main page) - https://cloud.google.com/vertex-ai/docs/start/introduction-unified-platform (docs entry point) - https://console.cloud.google.com/vertex-ai (cloud console). - Source: Hacker News / 5 months ago
Starting on December 13, developers and enterprise customers can access Gemini Pro via the Gemini API in Google AI Studio or Google Cloud Vertex AI. Source: 5 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 / 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
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
NumPy - NumPy is the fundamental package for scientific computing with Python
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
OpenCV - OpenCV is the world's biggest computer vision library