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1. 张量基础概念. 张量(Tensor)是PyTorch中的核心数据结构，可以看作是多维数组的扩展。 在PyTorch中，张量不仅用于存储数据，还是构建神经网络的基础组件。 1.1 张量的维度. 张量可以有不同的维度： 0维张量：标量（单个数字） 1维张量：向量. 2维张量：矩阵
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Beta1.1 概念层次解析. 人工智能（AI）：使机器模拟人类智能的广义领域. 机器学习（ML）：通过数据驱动的方法让系统自动改进性能. 深度学习（DL）：基于多层神经网络的机器学习子领域. 关系示意图： 人工智能 ⊃ 机器学习 ⊃ 深度学习. 二. PyTorch环境配置 2.1 Conda ...
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Betayolo v5使用gpu，目录一、环境安装测试二、数据集训练2.1yaml配置2.1.1数据集配置文件2.1.2 模型配置文件2.2VisDrone数据集训练实战2.2.1下载数据集2.2.2label转yolov52.2.3训练2.2.4可视化三、改成ROS节点四、加速训练4.1训练预热Warmup4.2余弦退火调整学习率 4.3自动计算锚框4.4超参数进化4.5自动混合
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BetaOur proposed SpectroMamba architecture is shown in Fig. 1.Given the input time series \(X = [x_1, x_2, \dots , x_L] \in \mathbb {R}^{R \times L}\), we first apply Reverse Instance Normalization (RevIN) [] to process the input, a method originally designed to address distributional shifts in the time domain.Next, we apply the extended Discrete Fourier Transform (DFT) to transform the data into ...
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BetaApple Machine Learning Research With the rapid expansion in the scale of large language models (LLMs), enabling efficient distributed inference across multiple computing units has
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BetaThe platform provides tailored strategies to minimize capital gains taxes, cut fund fees, boost passive income, and fine-tune portfolio allocation. For instance, saving just 1% on ETF and mutual fund fees could add $186,877 to a retirement fund, while reducing capital gains taxes by $10,221 could grow to $76,123 over 30 years through reinvestment.
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Beta文章目錄導包數據Dataloadercollat
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Beta反洗钱与合规：自动化报告生成_（10）.编程语言与软件工具.docx,PAGE 1 PAGE 1 编程语言与软件工具 在反洗钱与合规的自动化报告生成领域，选择合适的编程语言和软件工具是至关重要的。这些工具不仅能够帮助我们高效地处理和分析大量的金融交易数据，还能通过人工智能技术提高报告生成的准确性 ...
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Beta我想做的是少样本图像目标检测，我的异物数量只有200张，我想做改进yolov11的算法，请给我一些即插即用的模块或则改进yolov11的建议，我使用的是ultralytic库，我上传的图片是我直接用yolov11跑的算法结果，请进行分析，这个效果目前是怎样的，我现在的yaml文件如下：# Ultralytics A
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Beta(vllm) llm@aitt:/data_a/llm$ python collect_env.py INFO 05-23 10:07:58 [__init__.py:239] Automatically detected platform cuda. Collecting environment information... ===== System Info ===== OS : Ubuntu 20.04.4 LTS (x86_64) GCC version : (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0 Clang version : Could not collect CMake version : version 3.16.3 Libc version : glibc-2.31 ===== PyTorch Info ...
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