"I am a big fan of Coursera and attend lots of different courses. Time constraints don't allow me to attend all the courses I want at the same time. I came across your script, and I am very happily using it! Great stuff and thanks for making this available on Github - well done!
If you get an error like"YouTube said: Please sign in to view this video.", then we can't do much about it. You can try to pass your credentials toyoutube-dl(seehttps://github.com/rg3/youtube-dl#authentication-options) with the use ofedx-dl's option--youtube-dl-options. If it...
If you found this project useful, support the developer by buying them a coffee here: https://www.buymeacoffee.com/gurrrungor if you don't want to give monetary donations consider giving them a star ⭐ in Github. (It's free)https://github.com/gurrrung/coursera-HD-video-downloader...
datasciencecoursera:Coursera 课程数据的 Github 存储库 Scientist's Toolbox 行业研究 - 数据集Fa**te 上传3KB 文件格式 zip run_analysis.R 信息 一些描述脚本如何工作的注释如下: 假定所需的数据驻留在 R 工作目录中。 该脚本需要以下文件: activity_labels.txt 此文件包含描述性活动 features.txt 此文件包含...
昨天刚刚放假。准备这个暑假,把这个课程重新看一遍,预计10天时间。 编程作业放到了github上:coursera_machine_learning 1. Introduction 1.1 Supervised Learning 已知输入x以及其对应的标签y,求解 f:x→y 回归 regression:输出的结果y是一个连续的变量 y=ℝ 分类 classification:输出的结果... ...
1⃣. GitHub:世界上最大代码托管,很多开源项目; 2⃣. Tutorialspoint:实用编程知识; 3⃣. HackerRank:在线编程平台,参赛,测试自己 4⃣. edX:高质量计算机编程课程平台; 5⃣. Codecademy:交互式在线编程学习平台; 6⃣. FreeCodeCamp:在线编程学习社区 ...
1. GitHub:世界上最大代码托管,很多开源项目; 2. Tutorialspoint:实用编程知识; 3. HackerRank:在线编程平台,参赛,测试自己 4. edX:高质量计算机编程课程平台; 5. Codecademy:交互式在线编程学习平台; 6. FreeCodeCamp:在线编程学习社区 7. GeeksforGeeks:提供算法和数据结构教程; ...
(Object detection)3.4卷积的滑动窗口实现(Convolutional implementation of sliding windows)3.5Bounding Box预测(Bounding box predictions)3.6交并比(Intersection over union)3.7非极大值抑制(Non-maxsuppression)3.8Anchor Boxes3.9YOLO 算法(Putting it together: YOLO algorithm)3.10候选区域(选修)(Region proposals (...
Matlab 环境: 1. 一元线性回归 ex1.m 多元线性回归 ex1_multi.m 特征缩放 computeCostMulti and gradientDescent是没有变的。 正规方程法 源码: https://github.com/twomeng/linear-regression-
Introduction to tools that data analysts and data scientists work with such as version control, markdown, git, GitHub, R, and RStudio Set up R, R-Studio, Github and other useful tools R programming including reading data into R, accessing R packages, writing R functions, debugging, profiling...