加利福尼亚州洛杉矶。天使之城。廷塞尔敦。世界娱乐之都！以温暖的天气、棕榈树、绵延的海岸线和好莱坞而闻名，并制作了一些最具标志性的电影和歌曲。然而，与任何人口稠密的城市一样，它并不总是魅力四射，可能会有大量的犯罪。
Los Angeles, California . The City of Angels. Tinseltown. The Entertainment Capital of the World! Known for its warm weather, palm trees, sprawling coastline, and Hollywood, along with producing some of the most iconic films and songs. However, as with any highly populated city, it isn t always glamorous and there can be a large volume of crime. (2024-04-13, Jupyter Notebook, 0KB, 下载0次)
使用美国有线电视新闻网（CNN）对美国国家航空航天局（NASA）好奇号探测器在火星上拍摄的图像进行分类。前端界面是使用Streamlit开发的，为与分类模型交互提供了直观的用户体验。
Classifies images captured by NASA s Curiosity rover on Mars using CNN. The frontend interface is developed using Streamlit, providing an intuitive user experience for interacting with the classification model. (2024-03-31, Jupyter Notebook, 0KB, 下载0次)
根据Mehdi Mirza和Simon Osindero的研究论文《条件生成对抗网》，基于类标签为MNIST数字实现cGAN。利用PyTorch和详细的模型架构、训练管道和TensorBoard日志记录。
Implementing cGANs for MNIST digits based on class labels, following the research paper Conditional Generative Adversarial Nets by Mehdi Mirza and Simon Osindero. Utilizes PyTorch with detailed model architecture, training pipeline, and TensorBoard logging. (2024-03-24, Jupyter Notebook, 0KB, 下载0次)
使用张量流keras构建VGG16和GoogleLenet Archtechtures的运动识别成就VGG16:训练精度98%验证精度92%测试精度80%谷歌网：训练精度96%验证精度94%测试精度85%
sport recognition using tensorflow keras to bulid VGG16 and GoogLenet archetechtures Achievement VGG 16: Training Accuracy 98% Validation Accuracy 92% Test Accuracy 80% GoogleNet: Training Accuracy 96% Validation Accuracy 94% Test Accuracy 85% (2024-03-02, Jupyter Notebook, 0KB, 下载0次)
该存储库包含一个利用Selenium库的基于Python的web自动化项目。目的是从各种新闻网站上搜集与“Bolsonaro”一词相关的新闻文章，并提取相关链接以供进一步分析。
This repository houses a Python-based web automation project utilizing the Selenium library. The aim is to scrape news articles related to the term "Bolsonaro" from various news websites and extract relevant links for further analysis. (2024-01-30, Jupyter Notebook, 0KB, 下载0次)
分析Arbitrum、Optimism、Polygon和zkSync区块链的高级数据、走向市场的基本见解、顶级协议用户获取保留数据等（主网启动后的第一个100天）
Analyze high-level data, go-to-market essential insights, top protocol user acquisition-retention data, and more for Arbitrum, Optimism, Polygon, and zkSync blockchains (first 100 days post-mainnet launch) (2023-09-16, Jupyter Notebook, 0KB, 下载0次)
一些爬虫的学习笔记资料。必应图片下载爬虫、豆瓣读书爬虫、 当当图书爬虫、网易云用户信息爬虫、GitHub用户信息爬虫、 Twitter用户图片下载等等。
Some reptile learning notes. Bing Image Download Crawler, Douban Reading Crawler, Dangdang Book Crawler, Netease Cloud User Information Crawler, GitHub User Information Crawler, Twitter User Image Download, etc. (2021-07-15, Jupyter Notebook, 27076KB, 下载0次)
该混合入侵检测系统在CSE-CIC-IDS2018和TON-IoT两个公网数据集上进行了测试，结果表明，该系统具有良好的性能...
The proposed hybrid IDS is tested on two public network datasets, the CSE-CIC- IDS2018 and the TON IoT datasets, representing internal and external network traffic data. Various measures, such as accuracy, detection rates, false alarm rates, F1 scores, and model execution time, are used to assess the model s feasibility, efficacy, and efficiency.... (2022-05-18, Jupyter Notebook, 25KB, 下载0次)
创建了ML算法，使用暗网（神经网络框架）和...
Created ML algorithm that detects whether a person is wearing mask or not using darknet (neural network framework) & yolov3. The dataset was created by taking images from the internet and using labellimg to convert the boxes into text files. Trained the model & got the "last.weights" file using google colab, and ran the code on pycharm The (2021-04-12, Jupyter Notebook, 4KB, 下载0次)
是一次性的交易猎人，这些促销活动可能对销售额没有什么长期影响。此外，天猫网...
Merchants sometimes run big promotions (e.g., discounts or cash coupons) on particular dates (e.g., Boxing-day Sales, "Black Friday" or "Double 11 (Nov 11th)”, in order to attract a large number of new buyers. Unfortunately, many of the attracted buyers are one-time deal hunters, and these promotions may have little long lasting impact on (2018-01-31, Jupyter Notebook, 3276KB, 下载0次)
Python数据产品正在推动人工智能革命。像谷歌、脸书和网飞这样的顶级公司使用预测...
Python data products are powering the AI revolution. Top companies like Google, Facebook, and Netflix use predictive analytics to improve the products and services we use every day. Take your Python skills to the next level and learn to make accurate predictions with data-driven systems and deploy machine learning models with this four-course (2021-05-30, Jupyter Notebook, 2095KB, 下载0次)
使用python对慕课网的北京交通大学图像识别课程里介绍的算法(不只是课程设计!)用基础库,(不使用现成的图像识别库,如opencv等)实现一遍。
Use Python to implement the algorithm (not just course design!) introduced in the image recognition course at Beijing Jiaotong University on MOOC.com using a basic library (without using existing image recognition libraries such as OpenCV). (2022-03-24, Jupyter Notebook, 11968KB, 下载0次)
使用卷积神经网络和光学字符识别构建手写方程求解器。美国有线电视新闻网模型...
A Handwritten Equation Solver built using Convolutional Neural Network and Optical Character Recognition. CNN model is used for recognition of digits and symbols. OCR is used for processing the the image and segmentation. (2021-07-06, Jupyter Notebook, 7601KB, 下载0次)
Fund-review-Crawl-and-analysis,这是一个基金评论与股票市场的情感分析项目,目的是手动爬取天天基金网基民评论与东方财富网股市行情的资讯,从基民评论、重仓股票、市场行情三个方面出发,使用情感词典与LDA模型进行分析,从而做出是否值的购买基金的决策。带有标签clean的是...
Fund review Crowl and analysis is a sentiment analysis project for fund reviews and stock markets. The purpose is to manually crawl information from Tiantian Fund Network s funder reviews and Dongfang Wealth Network s stock market trends. Starting from three aspects: funder reviews, heavy stocks, and market trends, this project uses sentiment dictionaries and LDA models to analyze, in order to make a decision on whether to buy a fund for value. With the label clean (2023-04-30, Jupyter Notebook, 9527KB, 下载0次)
dog_bred_classification，这个项目是一个多类别的图像分类。我使用了TensorFlow `mobilenet_v2_130_224`（[https://tfhub.dev…]（https://tfhub_dev谷歌图像网mobilenet_v_22_130_224分类4）
dog_breed_classification,This project is a multi-class image classification. I have used TensorFlow `mobilenet_v2_130_224` ([https: tfhub.dev …](https: tfhub.dev google imagenet mobilenet_v2_130_224 classification 4) (2021-01-04, Jupyter Notebook, 0KB, 下载0次)
视频压缩网，一种新的视频压缩方法，通过改进传统方法的缺点，并取代每种传统方法...
A new approach to video compression by refining the shortcomings of conventional approach and substituting each traditional component with their neural network counterpart. Our proposed work consists of motion estimation, compression and compensation and residue compression, learned end-to-end to minimize the rate-distortion trade off. The (2021-03-07, Jupyter Notebook, 219456KB, 下载0次)
用于一次图像识别的暹罗神经网络，一次暹罗神经网，使用TensorFlow 2.0，基于Gregory Koch、Richard Zemel和...
One-shot Siamese Neural Network, using TensorFlow 2.0, based on the work presented by Gregory Koch, Richard Zemel, and Ruslan Salakhutdinov. we used the “Labeled Faces in the Wild” dataset with over 5,700 different people. Some people have a single image, while others have dozens. (2022-06-25, Jupyter Notebook, 1162KB, 下载0次)
Smart-network,无线根因分析结合现网历史告警和故障定位工单数据,通过机器学习手段建立故障根因分析模型,快速定位故障原因,大幅提升网络运维效率。
Smart network, combining wireless root cause analysis with existing network historical alarms and fault location work order data, establishes a fault root cause analysis model through machine learning methods, quickly locates the fault cause, and significantly improves network operation and maintenance efficiency. (2019-08-23, Jupyter Notebook, 23761KB, 下载0次)
Python3machinelearning-note,慕课网liuyubobobo的Python3机器学习手打笔记 课件 源码资料。喜欢的点个star,目前还没有更新完,会一直更新。
Python 3 machine learning note, the source code material for the Python 3 machine learning hand note taking courseware from Muke.com liuyubobobo. Click star if you like, it has not been updated yet and will continue to be updated. (2020-07-13, Jupyter Notebook, 6777KB, 下载0次)
使用GoogleColab进行深度学习，深度学习应用程序（暗网-YOLOv3，YOLOv4|DeOldify-图像着色，视频着色|人脸识别...
Deep Learning Applications (Darknet - YOLOv3, YOLOv4 | DeOldify - Image Colorization, Video Colorization | Face-Recognition) with Google Colaboratory - on the free Tesla K80/Tesla T4/Tesla P100 GPU - using Keras, Tensorflow and PyTorch. (2020-04-27, Jupyter Notebook, 49026KB, 下载0次)