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)
“探索对44种脑肿瘤类型进行分类的MRI图像的rad集合！从星形细胞瘤到胶质母细胞瘤，我们的数据集具有T1、对比度T1和T2图像，非常适合ML爱好者和医学研究人员。没有患者ID，只有医生解释的酷酷扫描。投入到脑力娱乐和学习中吧！”
"Explore a rad collection of MRI images categorizing 44 brain tumor types! From astrocytoma to glioblastoma, our dataset features T1, contrast T1, and T2 images, perfect for ML enthusiasts and medical researchers. No patient IDs, just cool scans interpreted by doctors. Dive in for brainy fun and learning!" (2024-02-24, Jupyter Notebook, 0KB, 下载0次)
欢迎来到我们的Python课程，该课程专为有兴趣从事数据科学或人工智能职业的初学者设计。我受到了伟大导师的启发#感谢JMM Technology的高级数据科学家Sikandermir爵士、DigiTech Synergy的首席执行官Waqas爵士和Wajuullah Bukhari爵士。
Welcome to our Python course designed specifically for beginners who are interested in pursuing a career in Data Science or AI.. I am inspired by my great mentors # Thanks to Sir Sikandermir Senior Datascientist at JMM Technology , Sir Waqas CEO of DigiTech Synergy & Sir Wajiullah Bukhari. (2024-02-08, Jupyter Notebook, 0KB, 下载0次)
在这项研究中，我们提出了一种利用挤压和激发密度网（SEDenseNet）架构来促进肾脏疾病的治疗的方法...
In this study, we present an approach that utilizes the Squeeze and Excitation DenseNet (SEDenseNet) architecture to advance kidney disease analysis through image processing. The obtained outcome, specifically the accuracy rate, has been measured at an impressive 99.56%. (2023-11-22, Jupyter Notebook, 0KB, 下载0次)
献血拯救生命。我们的项目使用DL与RNN和共关系网络来识别高风险捐赠者，并增强风险评估...，
Blood donation saves lives. Our project employs DL with RNN and co-relational networks to identify high-risk donors and enhance risk assessment accuracy for better donor planning. (2023-08-30, Jupyter Notebook, 0KB, 下载0次)
一种将用暗网训练的yolov3微型模型转换为Unity的梭鱼格式的方法，该方法将实际导入Unity，
A way to convert a yolov3 tiny model trained with darknet to Unity s barracuda format in a way that will actually import into Unity, (2021-05-17, Jupyter Notebook, 0KB, 下载0次)
在这种环境下，两个代理控制球拍，使球在网上反弹。如果代理将球击过网，它将获得奖励...，
In this environment, two agents control rackets to bounce a ball over a net. If an agent hits the ball over the net, it receives a reward of +0.1. If an agent lets a ball hit the ground or hits the ball out of bounds, it receives a reward of -0.01. Thus, the goal of each agent is to keep the ball in play. The observation space consists of 8 (2020-09-12, Jupyter Notebook, 0KB, 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)
“创新网在线招聘黑客马拉松：用人工智能拯救生命”，其中疾病名称必须从文件中提取。...
"Innoplexus Online Hiring Hackathon: Saving lives with AI" where disease name has to be extracted from documents. The solution employes a Time distributed BI-LSTM model to perform Named Entity Recognition with 77.8% F1 score. (2019-04-19, Jupyter Notebook, 40KB, 下载0次)
垃圾类型检测软件，通过计算机视觉对垃圾进行分类。其中包括一个基于ssd移动网的深度学习模型和一个基于kivy的GUI...
Classify trash by computer vision. A ssd-mobilenet based deep learning model and a kivy based GUI is included in this repository. Currently, the software can detect bottles in video frame (2020-10-01, Jupyter Notebook, 33117KB, 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)
生成对抗性网络GANs专业化，深度学习解决方案。AI生成对抗性网（GANs）专业化
Generative-Adversarial-Networks-GANs-Specialization,Solutions to DeepLearning.AI Generative Adversarial Networks (GANs) Specialization (2020-10-11, Jupyter Notebook, 96582KB, 下载0次)
Coursera-Deep-Learning-deeplearning.ai,(完结)网易云课堂微专业《深度学习工程师》听课笔记,编程作业和课后练习
Coursera Deep-Learning Deepearning.ai, (Completed) NetEase Cloud Classroom Micro Professional "Deep Learning Engineer" Listening Notes, Programming Assignments, and After Class Exercises (2019-01-21, Jupyter Notebook, 467453KB, 下载0次)
machine_learning_projects,网易微专业《数据分析师》机器学习项目部分,包括特征处理、参数优化、上下采样、中文分词和项目案例模板的内容
machine_ learning_ Projects, part of the NetEase Micro Professional "Data Analyst" machine learning project, including feature processing, parameter optimization, up and down sampling, Chinese word segmentation, and project case templates (2020-11-19, Jupyter Notebook, 86557KB, 下载0次)
machine_learning_algorithm,网易微专业《数据分析师》机器学习算法部分,包括Josh Hug和唐宇迪老师的算法代码,有大量算法示例图片
machine_ learning_ Algorithm, the machine learning algorithm section of NetEase Micro Professional s "Data Analyst", including algorithm code from Josh Hug and Teacher Tang Yudi, with a large number of algorithm example images (2020-10-20, Jupyter Notebook, 29332KB, 下载0次)
Human-Activity-Recognition-Based-on-Machine-Learning,机器学习实现基于手机六轴数据的人体动作识别和计数功能。并利用云服务器和微信小程序在手机上实现。 Use machine learning to achieve human activity recognition and counti...
Human Activity Recognition Based on Machine Learning, machine learning enables human motion recognition and counting based on six axis data from mobile phones. And implement it on mobile phones using cloud servers and WeChat mini programs. Use machine learning to achieve human activity recognition and counti... (2022-12-26, Jupyter Notebook, 17559KB, 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)
DCGAN_generate_anime_pictures,生成对抗网咯(GAN)是一类在无监督学习中使用的神经网络,其有助于解决按文本生成图像、提高图片分辨率、药物匹配、检索特定模式的图片等任务。本库包含利用DCGAN生成动漫图片项目资源及代码。
DCGAN_ generate_ anime_ Pictures, Generated Antagonism Network (GAN) is a kind of neural network used in unsupervised learning, which helps to solve the tasks of generating images according to text, improving image resolution, drug matching, and retrieving images of specific patterns. This library contains project resources and code for generating anime images using DCGAN. (2020-02-28, Jupyter Notebook, 295521KB, 下载0次)