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TensorFlow
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Gitmore represents a thoughtful approach to democratizing Git repository intelligence, successfully addressing the common challenge of extracting actionable insights from complex development activities. The platformโs combination of AI-powered analysis, cross-platform compatibility, and business-friendly reporting creates compelling value for teams seeking to improve visibility into development progress without investing in comprehensive engineering analytics platforms.
Based on our record, Gitmore.io should be more popular than TensorFlow. It has been mentiond 22 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.
The open-source movement offers hope here. Projects like Hugging Face are democratizing access to state-of-the-art models, while initiatives like Google's TensorFlow provide powerful frameworks without licensing costs. But even open-source solutions require technical expertise that many lack. - Source: dev.to / 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 / over 3 years 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: about 4 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 4 years ago
I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org. Source: over 4 years ago
Every commit has a message. Every PR has a title and description. The status update already exists. It's just locked in GitHub. Who this is for: - Founders updating investors - PMs writing release notes - CEOs who want visibility without standups - Anyone who asks "what shipped?" and waits for an engineer to respond What it does: Connect your repos. Ask questions: - "What shipped this month?" - "Who... - Source: Hacker News / 7 months ago
Gitmore (https://gitmore.io) โ natural language queries across GitHub, GitLab, and Bitbucket. Instead of filtering PRs, scanning commit logs, or asking engineers for updates: - "What shipped last week?" - "Who's been working on the API?" - "Which PRs have been open longest?" - "Summarize this month's releases" Plain English in, plain English out. How it works: Connect your repos via OAuth. We register... - Source: Hacker News / 7 months ago
If you're a founder who doesn't code, you probably rely on engineers to tell you what's shipping. That works until investors ask for updates, customers want a changelog, or you just need to know where things stand. What it does: Connect your repos. Ask questions: "What shipped last week?" "What's in progress?" "Who worked on what?" Get plain English answers from your commit history. Automated reports: Schedule... - Source: Hacker News / 7 months ago
Gitmore (https://gitmore.io) One feature I built that's been useful: a Slack bot that queries your Git history. Connect your repos. Add the bot to Slack. Ask:. - Source: Hacker News / 7 months ago
- 2FA support GitHub, GitLab, Bitbucket โ one dashboard. Free for 1 repo: https://gitmore.io How do you currently handle investor questions about engineering progress? - Source: Hacker News / 7 months ago
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Waydev - Waydev analyzes your codebase from Github, Gitlab, Azure DevOps & Bitbucket to help you bring out the best in your engineers work.
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
IBM Watson Studio - Learn more about Watson Studio. Increase productivity by giving your team a single environment to work with the best of open source and IBM software, to build and deploy an AI solution.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Azure Machine Learning Service - Build and deploy machine learning models in a simplified way with Azure Machine Learning service. Make machine learning more accessible with automated capabilities.