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Based on our record, PyTorch should be more popular than Google Cloud Machine Learning. It has been mentiond 106 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.
TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more... - Source: dev.to / 12 days ago
*My post explains Dot, Matrix and Element-wise multiplication in PyTorch. - Source: dev.to / about 2 months ago
Import torch # we use PyTorch: https://pytorch.org Data = torch.tensor(encode(text), dtype=torch.long) Print(data.shape, data.dtype) Print(data[:1000]) # the 1000 characters we looked at earlier will to the GPT look like this. - Source: dev.to / 2 months ago
AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries. - Source: dev.to / about 2 months ago
Which label applies to a tool sometimes depends on what you do with it. For example, PyTorch or TensorFlow can be called a library, a toolkit, or a machine-learning framework. - Source: dev.to / about 2 months ago
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 / 3 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
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
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
OpenCV - OpenCV is the world's biggest computer vision library