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Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.

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NoteDance / Note

Star 42

Easily implement parallel training and distributed training. Machine learning library. Note.neuralnetwork.tf package include Llama2, Llama3, Gemma, CLIP, ViT, ConvNeXt, BEiT, Swin Transformer, Segformer, etc, these models built with Note are compatible with TensorFlow and can be trained with TensorFlow.

python machine-learning reinforcement-learning deep-learning neural-network tensorflow ml deep-reinforcement-learning pytorch artificial-intelligence rl machinelearning deeplearning dl neuralnetwork drl distributed-training reinforcementlearning parallel-training deepreinforcementlearning
  • Updated Jun 11, 2024
  • Python

aws-solutions-library-samples / guidance-for-machine-learning-inference-on-aws

Star 32

This Guidance demonstrates how to deploy a machine learning inference architecture on Amazon Elastic Kubernetes Service (Amazon EKS). It addresses the basic implementation requirements as well as ways you can pack thousands of unique PyTorch deep learning (DL) models into a scalable architecture and evaluate performance at scale

ml eks-cluster mlops-workflow inferentia graviton3
  • Updated Jun 10, 2024
  • Shell

activeloopai / deeplake

Star 7.8k

Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai

python data-science machine-learning ai computer-vision deep-learning tensorflow cv image-processing ml pytorch datasets data-version-control datalake mlops vector-search vector-database large-language-models llm langchain
  • Updated Jun 10, 2024
  • Python
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