这是一种用于实验室地震检测和相位拾取的集成深度学习模型（AEbagging），对当前模型仍有许多改进。如果我们可以将不同的AE数据集合并到我们的模型中，它不仅增强了模型的鲁棒性，而且消除了由信噪比施加的约束。
This is an ensemble deep learning model (AEbagging) for laboratory earthquake detection and phase picking, with many improvements still to be made to the current model. If we can incorporate diverse AE datasets into our model, it not only enhances the robustness of the model but also removes the constraints imposed by signal-to-noise ratio. (2024-03-04, Jupyter Notebook, 0KB, 下载0次)
该知识库包含对印度初创企业生态系统的分析，为在......中做出明智的决策提供见解...，
This repository contains the analysis of the Indian startup ecosystem to provide insights for making informed decisions in venturing into this domain. The analysis includes exploring funding patterns, sector-wise distribution, geographical location impact on funding, trends over time and correlations between various factors. (2023-07-14, Jupyter Notebook, 0KB, 下载0次)
2023年安永开放科学数据挑战-作物预测的目标是使用卫星图像预测稻田产量...，
Predicting rice field yields through the integration of Microsoft Planetary satellite images, meteorological data, and field information in the 2023 EY Open Science Data Challenge - Crop Forecasting. (2023-05-27, Jupyter Notebook, 0KB, 下载0次)
测量墨西哥城的气象灾害，
Measure meteorological disasters in Mexico city, (2021-07-30, Jupyter Notebook, 0KB, 下载0次)