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Top 10 Machine Learning Tools
Machine learning is quickly becoming the standard in many industries, from self-driving cars to targeted ads. As organizations realize the…
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Introduction to Model Monitoring
Deploying your models into production is only half the battle in machine learning. Once a model moves to the production…
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Guide To Distributed Machine Learning
How can complex models with millions of parameters be trained on terabytes of datasets? Training large-size models with traditional methods…
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Resources for building better recommender systems
Building recommenders isn’t always easy. With input from Jacopo Tagliabue, Ronay Ak from Nvidia, and Serdar Kadioglu from Fidelity,…
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Kangas: Visualize Multimedia Data at Scale
Thousands of data scientists use Comet panels, histograms, and reports to visualize data from experiments every day. While we’re proud…
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“Text-to-Color” from Scratch with CLIP, PyTorch, and Hugging Face Spaces
Example input and output from the Gradio app built using the Text to Color model. Moving from left to right,…
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Using CLIP and Gradio to assess similarity between text prompts and ranges of colors
Link to Colab notebook Hugging Face Space Intro OpenAI’s CLIP model and related techniques have taken the field of machine…
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Weight Initialization In Deep Neural Networks
Photo by Graphic Node on Unsplash Very deep neural networks can suffer from either vanishing or exploding gradients. This is because the main operation…
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Using TensorFlow in Comet
Photo by Alex Knight on Unsplash Neural Networks are a subset of artificial intelligence, aiming at modeling the human brain through mathematical concepts.…
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New Integration: Comet and Ray
We’re excited to announce another excellent integration with Comet — Ray! This integration allows data scientists to leverage Comet’s experiment tracking…
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Comet Blog
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From Observability to Optimization: Announcing the Opik Agent Optimizer Public Beta
At Comet, we’re driven by a commitment to advance innovation in AI, particularly in the realm of LLM observability. Our…
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