ml
์ด 19๊ฐ์ ์ํค ยท 1 / 1 ํ์ด์ง ๐ก RSS ๐ธ๏ธ ๊ทธ๋ํ
- ๋ถ์ฐ ํ์ต#ai #training #parallelism #scaling
- HBM#hardware #memory #gpu #tpu #dram
- SIMT#gpu #parallel-computing #architecture #cuda
- SPMD#parallel-computing #programming-model #distributed
- GPU: ๊ทธ๋ํฝ/ML ๋ณ๋ ฌ ํ๋ก์ธ์#ml #hardware #gpu #cuda #tensor-core #simt
- NPU (Neural Processing Unit): ์ฃ์ง AI ์นฉ#ml #hardware #npu #edge #inference #quantization
- Systolic Array#hardware #tpu #architecture #matrix-multiply #gemm
- TPU (Tensor Processing Unit): Google ์ ML ASIC#ml #hardware #tpu #google #asic #xla
- [FL] FedAvg (Federated Averaging)#ml #federated-learning #distributed #algorithm
- [FL] Frameworks (Flower, TFF, NVFlare, FATE, PySyft)#ml #federated-learning #framework #tooling
- [FL] Non-IID Data & Client Drift#ml #federated-learning #distributed #non-iid
- [FL] Personalized Federated Learning#ml #federated-learning #personalization #meta-learning
- [FL] Secure Aggregation#ml #federated-learning #privacy #cryptography #security
- [AWS SageMaker] Model Monitor: ๋ชจ๋ธ ๋ฐ ๋ฐ์ดํฐ ๋๋ฆฌํํธ ๊ฐ์ง#aws #sagemaker #mlops #monitoring #drift
- Differential Privacy: (ฮต, ฮด) ๋ก ์ ๋ํํ๋ ํ๋ผ์ด๋ฒ์ ๋ณด์ฅ#ml #privacy #security #cryptography #dp
- Federated Learning: ๋ถ์ฐ ํ์ต without central data#ml #distributed #privacy #federated-learning #edge
- Transfer Learning: pre-training, fine-tuning, domain adaptation#ml #deep-learning #transfer-learning #fine-tuning #foundation-model
- ๋ถ๋ฅ ๋ชจ๋ธ ์งํ: Confusion Matrix, Precision, Recall, F1#ml #evaluation #classification #metrics
- ๋ชจ๋ธ ์์ํ#ai #model-compression #inference #machine-learning