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PyTorch 2.9 is now available, introducing key updates to performance, portability, and the developer experience. This release includes a stable libtorch ABI for C++/CUDA extensions, symmetric memory for multi-GPU kernels, expanded wheel support to include ROCm, XPU, and CUDA 13,…
🔥Kangas It is a tool for exploring, analyzing, and visualizing large-scale multimedia data. It provides a straightforward Python API for logging large tables of data, along with an intuitive visual interface for performing complex queries against your dataset. The key…
🚀 Data distribution shifts after model deployment! A common problem that often occurs after model deployment is Data Distribution Shifts. It refers to the differences between the distribution of data on which a model was trained and the distribution of data it encounters in the…
🔥 Text Distance It is a Python library for comparing distance between two or more sequences by many algorithms. Features: - 30+ algorithms - Pure python implementation - Simple usage - More than two sequences comparing - Some algorithms have more than one implementation in one…
⚡ Similarity Search across millions of vector embeddings is both computationally and memory-intensive. With Facebook's Faiss, you can optimize the vector search using optimized indexing with compression algorithms. In the video, I've discussed and implemented how to optimize…
🔥 FlashLight It is a fast, flexible machine learning library written entirely in C++. Core features: - Total internal modifiability, including internal APIs for tensor computation. - A small footprint, with the core clocking in at under 10 MB and 20k lines of C++. -…
Donald Trump, as President, is misusing his power to gamble with the Global Economy. #Trump #bitcoin
🔥 cuVs All vector databases use algorithms implemented by cuVS. It is a new library mostly derived from the approximate nearest neighbors and clustering algorithms in the RAPIDS RAFT library of machine learning and data mining primitives. It contains the most fully-featured…
🔥 BytePS - A high-performance and general distributed training framework. - Supports TensorFlow, Keras, PyTorch, and MXNet. - Runs on TCP or RDMA network. - It outperforms existing open-sourced distributed training frameworks by a large margin
🔥 Flyte - It is an open-source orchestrator that facilitates building production-grade data and ML pipelines. - It is built for scalability and reproducibility, leveraging Kubernetes as its underlying platform. - With Flyte, user teams can construct pipelines using the Python…
🔥 PyG (PyTorch Geometric) PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data. It consists of various methods for deep learning on graphs and other irregular…
🔥 ONNX Open Neural Network Exchange (ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. It provides an open-source format for AI models, both deep learning and traditional ML. It defines an extensible computation graph…
📢 Highly recommend five AI/ML courses 🚀 AI For Everyone ((DeepLearning.AI/Coursera)):Focus: A great starting point for non-technical audiences to understand AI concepts, applications, and how it impacts society. Key Takeaway: Provides a conceptual understanding of AI without…
🔥 Nanotron It is a library for pretraining transformer models. It provides a simple and flexible API to pretrain models on custom datasets. It is designed to be easy to use, fast, and scalable.
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