论文地址:DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning 1. R1关键贡献 DeepSeek-R1-Zero模型是一个纯粹通过强化学习来增强的强推理模型,摆脱了传统使用SFT训练所需的海量标注数据,同时使用基于规则的reward计算方式,解决了传统强化学习中引入基于模型的reward计算方式带来的reward h...
Dice Score: 2 * (Pred ∩ GT)/(Pred + GT) ROC, AUC: Log loss: 🔥 Train Learning Rate How big the steps are during training. Max LR: Compute it with LR Finder (lr_find()) LR schedule: Constant: Never use. Reduce it gradually: By steps, by a decay factor, with LR annealing...
11JJChina / deeplearning_ai_books 122Taideng / deeplearning_ai_books 12301098-Heminghui / deeplearning_ai_books 151706061 / deeplearning_ai_books 1ee7 / deeplearning_ai_books 2012fang1 / deeplearning_ai_books 2020zyc / deeplearning_ai_books 253627764 / deeplearning_ai_books 30750...
Learn how deep learning relates to machine learning and AI. In Azure Machine Learning, use deep learning models for fraud detection, object detection, and more.
Learn how deep learning works and how to use deep learning to design smart systems in a variety of applications. Resources include videos, examples, and documentation.
In this study, we applied two novel deep learning algorithms, the recurrent neural network (RNN) and convolutional neural network (CNN), for national-scale landslide susceptibility mapping of Iran. We prepared a dataset comprising 4069 historical landslide locations and 11 conditioning factors (...
1、一上来就自己动手写模型。建议首先用成熟的开源项目及其默认配置（例如 Gluon 对经典模型的各种复现、...
(1) What were the characteristics of the databases involved in reported studies? (2) What deep learning model architectures were included in reported studies? (3) How were these deep learning model architectures used in reported studies? (4) What classification performance has been achieved? (5)...
He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–17 Cetinkaya E, Amirpour H, Ghanbari M, Timmerer C (2021) CTU depth decision algorithms for HEVC: a survey. Signal Process: Image ...
Training to Convergence Deploying AI in real-world applications requires training networks to convergence at a specified accuracy. This is the best methodology to test whether AI systems are ready to be deployed in the field to deliver meaningful results. ...