Related Issues (20)
- [DAY 34] Instance/Panoptic segmentation and landmark localization & Conditional Generative Model
- [DAY 35] Multimodal captioning and speaking & 3D understanding HOT 1
- [원딜] pth → onnx → pth 순으로 모델을 저장할 때 마지막 pth 파일의 크기가 커지는 이유?
- [DAY 36] Lightweight models & The flip-side of the coin: on-device AI & Optimization
- [원딜] Gaussian Process HOT 2
- [DAY 37] Timespace of ML model & Compression
- [DAY 38] Acceleration & Pruning for network compression
- [DAY 39] Quantization for model compression & Knowledge distillation for network compression HOT 3
- [DAY 40] Low-rank approximation for model compression & Retrospect
- [DAY 24] 정점 표현 & 추천시스템 (심화) HOT 1
- [히스] CNN 과 GNN HOT 1
- [DAY 25] GNN 기초 & GNN 심화 HOT 1
- [DAY 27] 서비스 향 AI 모델 개발하기 & AI 시대의 커리어 빌딩
- [DAY 28] 캐글 그랜드마스터의 경진대회 노하우 대방출 & Full Stack ML Engineer
- [DAY 29] 자연어 처리를 위한 언어 모델의 학습과 평가 & 내가 만든 AI 모델은 합법일까?
- [DAY 30] AI + ML 과 Quant Trading & AI Ethics
- [DAY 31] CV - 이미지 분류 1 & 적은 수의 데이터를 효율적으로 학습하는 방법
- [DAY 32] CV - 이미지 분류 2 & Semantic segmentation
- [DAY 33] Object detection & CNN Visualization
- [샐리] (CV, CH06) Faster RCNN - class layer의 파라미터 수가 2k인 이유
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