Deep learning optimization algorithms + other resources
We're shooting over April's batch of news from our blog. You can find here something about algorithm optimization, LLM, the best tools on the 2024 market, and a new podcast episode on building ML Platform at Uber!?
Hope you find something useful!
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Case studies & practical MLOps
>?13 Best Tools for ML Experiment Tracking and Management in 2024 ?-?If you're curious about which experiment tracking tool to select, this article can be helpful. We review and compare the top tools for managing and tracking ML experiments, highlighting their key features and differences.
>?Best Tools For ML Model Serving ?- Let's not forget that choosing the right model-serving tool is also crucial for the success of any machine learning project. In this post, you can check different tools from BentoML to DeepSparse, compare their features, and ideal use cases.
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Guides & tutorials
>?Deep Learning Optimization Algorithms ?-?In this article,?Alessandro Lamberti discusses the most commonly used deep learning optimization algorithms, including Gradient Descent, Stochastic Gradient Descent, and the Adam optimizer. By the end of this post, you will have a clear idea of how to choose the best algorithm for training your models.
>?Customizing LLM Output: Post-Processing Techniques - Lastly, but certainly not least interesting, is the topic of LLM. This article allows you to discover effective post-processing techniques for LLMs, explore advanced sampling constraints, and learn about practical tools for customizing outputs.
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领英推荐
Tools
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ML Platform Podcast
> We're back with a new portion of the ML Platform Podcast!
On this episode, Mike Del Balso is our guest. Mike shares insights on his journey from Google to Tecton, building the ML platform (Michelangelo) at Uber, feature platforms, vector databases, and the future of the MLOps space in the world of foundational models.
To get notifications about new episodes, follow us on Spotify , Apple Podcasts , or subscribe to our YouTube channel .
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Okay, that's it for today. Hope you find these useful!
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Cheers!