[FTUForum.com] [UDEMY] Deep Learning Prerequisites Linear Regression in Python [FTU]

磁力链接/BT种子名称

[FTUForum.com] [UDEMY] Deep Learning Prerequisites Linear Regression in Python [FTU]

磁力链接/BT种子简介

种子哈希：b62ba45397ca5d56ca69de0d05850a70f673e212
文件大小：999.52M
已经下载：2354次
下载速度：极快
收录时间：2020-01-27
最近下载：2025-09-10

地址随时变，回家记住路

小野猫.com黑猫警长.com哆啦a猫.com御猫.com科目三.com猫哭老鼠.com女猫.com☜☜☜找最新地址请保存左面网址

磁力链接

magnet:?xt=urn:btih:B62BA45397CA5D56CA69DE0D05850A70F673E212
推荐使用PIKPAK网盘下载资源，PIKPAK是目前最好用网盘，10T超大空间，不和谐任何资源，支持无限次数离线下载，视频在线观看

下载BT种子文件

磁力链接 迅雷下载 在线观看 世界之窗 含羞草 极乐禁地 91视频 51品茶 逼哩逼哩 萝莉岛 欲漫涩 91短视频 成人快手 抖阴破解版 ai色色 pilipili 草榴社区 哆哔涩漫 好色先生 疯马秀 TikTok成人版 悠悠禁区 波多 听泉鉴鲍 xvideo 外网天堂 PornHub 抖音Max 呦乐园 拔萝卜 糖心视频 麻豆Vlog 暗网Xvideo

资源截图

API Integration

最近搜索

文件列表

  • 6. Appendix/3. Windows-Focused Environment Setup 2018.mp4 195.3 MB
  • 6. Appendix/11. What order should I take your courses in (part 2).mp4 85.6 MB
  • 6. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
  • 6. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
  • 6. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
  • 6. Appendix/11. What order should I take your courses in (part 2).vtt 39.5 MB
  • 3. Multiple linear regression and polynomial regression/2. Define the multi-dimensional problem and derive the solution.mp4 37.8 MB
  • 1. Welcome/1. Welcome.mp4 33.6 MB
  • 6. Appendix/10. What order should I take your courses in (part 1).mp4 30.7 MB
  • 1. Welcome/2. Introduction and Outline.mp4 29.8 MB
  • 2. 1-D Linear Regression Theory and Code/2. Define the model in 1-D, derive the solution.mp4 25.9 MB
  • 6. Appendix/5. How to Code by Yourself (part 1).mp4 25.7 MB
  • 4. Practical machine learning issues/11. Gradient Descent Tutorial.mp4 23.9 MB
  • 2. 1-D Linear Regression Theory and Code/1. Define the model in 1-D, derive the solution (Updated Version).mp4 20.3 MB
  • 6. Appendix/7. How to Succeed in this Course (Long Version).mp4 19.2 MB
  • 2. 1-D Linear Regression Theory and Code/7. Demonstrating Moore's Law in Code.mp4 18.3 MB
  • 4. Practical machine learning issues/4. Generalization and Overfitting Demonstration in Code.mp4 18.1 MB
  • 6. Appendix/12. Python 2 vs Python 3.mp4 17.7 MB
  • 3. Multiple linear regression and polynomial regression/5. Polynomial regression - extending linear regression (with Python code).mp4 17.2 MB
  • 3. Multiple linear regression and polynomial regression/4. Coding the multi-dimensional solution in Python.mp4 15.6 MB
  • 6. Appendix/6. How to Code by Yourself (part 2).mp4 15.5 MB
  • 2. 1-D Linear Regression Theory and Code/3. Coding the 1-D solution in Python.mp4 15.1 MB
  • 3. Multiple linear regression and polynomial regression/1. Define the multi-dimensional problem and derive the solution (Updated Version).mp4 15.1 MB
  • 3. Multiple linear regression and polynomial regression/6. Predicting Systolic Blood Pressure from Age and Weight.mp4 12.9 MB
  • 2. 1-D Linear Regression Theory and Code/5. Determine how good the model is - r-squared.mp4 11.9 MB
  • 4. Practical machine learning issues/1. What do all these letters mean.mp4 10.1 MB
  • 4. Practical machine learning issues/13. Bypass the Dummy Variable Trap with Gradient Descent.mp4 8.9 MB
  • 1. Welcome/3. What is machine learning How does linear regression play a role.mp4 8.8 MB
  • 4. Practical machine learning issues/15. L1 Regularization - Code.mp4 8.7 MB
  • 4. Practical machine learning issues/5. Categorical inputs.mp4 8.6 MB
  • 4. Practical machine learning issues/7. Probabilistic Interpretation of Squared Error.mp4 8.5 MB
  • 5. Conclusion and Next Steps/1. Brief overview of advanced linear regression and machine learning topics.mp4 8.5 MB
  • 4. Practical machine learning issues/9. L2 Regularization - Code.mp4 8.5 MB
  • 5. Conclusion and Next Steps/2. Exercises, practice, and how to get good at this.mp4 7.5 MB
  • 4. Practical machine learning issues/8. L2 Regularization - Theory.mp4 7.0 MB
  • 4. Practical machine learning issues/10. The Dummy Variable Trap.mp4 6.4 MB
  • 4. Practical machine learning issues/2. Interpreting the Weights.mp4 6.3 MB
  • 6. Appendix/1. What is the Appendix.mp4 5.7 MB
  • 4. Practical machine learning issues/16. L1 vs L2 Regularization.mp4 5.0 MB
  • 4. Practical machine learning issues/14. L1 Regularization - Theory.mp4 4.9 MB
  • 2. 1-D Linear Regression Theory and Code/6. R-squared in code.mp4 4.7 MB
  • 1. Welcome/4. Introduction to Moore's Law Problem.mp4 4.6 MB
  • 4. Practical machine learning issues/3. Generalization error, train and test sets.mp4 4.6 MB
  • 6. Appendix/2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 4.2 MB
  • 4. Practical machine learning issues/6. One-Hot Encoding Quiz.mp4 4.0 MB
  • 4. Practical machine learning issues/12. Gradient Descent for Linear Regression.mp4 3.7 MB
  • 3. Multiple linear regression and polynomial regression/7. R-squared Quiz 2.mp4 3.7 MB
  • 1. Welcome/6. How to Succeed in this Course.mp4 3.5 MB
  • 3. Multiple linear regression and polynomial regression/3. How to solve multiple linear regression using only matrices.mp4 3.3 MB
  • 2. 1-D Linear Regression Theory and Code/8. R-squared Quiz 1.mp4 2.9 MB
  • 2. 1-D Linear Regression Theory and Code/4. Exercise Theory vs. Code.mp4 1.1 MB
  • 6. Appendix/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 28.4 kB
  • 6. Appendix/5. How to Code by Yourself (part 1).vtt 20.3 kB
  • 6. Appendix/3. Windows-Focused Environment Setup 2018.vtt 17.8 kB
  • 2. 1-D Linear Regression Theory and Code/1. Define the model in 1-D, derive the solution (Updated Version).vtt 14.7 kB
  • 6. Appendix/10. What order should I take your courses in (part 1).vtt 14.4 kB
  • 6. Appendix/7. How to Succeed in this Course (Long Version).vtt 13.1 kB
  • 6. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt 12.7 kB
  • 6. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.vtt 12.5 kB
  • 6. Appendix/6. How to Code by Yourself (part 2).vtt 11.9 kB
  • 3. Multiple linear regression and polynomial regression/2. Define the multi-dimensional problem and derive the solution.vtt 11.6 kB
  • 3. Multiple linear regression and polynomial regression/1. Define the multi-dimensional problem and derive the solution (Updated Version).vtt 10.5 kB
  • 2. 1-D Linear Regression Theory and Code/2. Define the model in 1-D, derive the solution.vtt 9.8 kB
  • 4. Practical machine learning issues/4. Generalization and Overfitting Demonstration in Code.vtt 8.4 kB
  • 4. Practical machine learning issues/1. What do all these letters mean.vtt 7.2 kB
  • 2. 1-D Linear Regression Theory and Code/7. Demonstrating Moore's Law in Code.vtt 6.3 kB
  • 4. Practical machine learning issues/7. Probabilistic Interpretation of Squared Error.vtt 5.8 kB
  • 6. Appendix/12. Python 2 vs Python 3.vtt 5.5 kB
  • 1. Welcome/2. Introduction and Outline.vtt 5.4 kB
  • 1. Welcome/3. What is machine learning How does linear regression play a role.vtt 5.4 kB
  • 5. Conclusion and Next Steps/1. Brief overview of advanced linear regression and machine learning topics.vtt 5.2 kB
  • 3. Multiple linear regression and polynomial regression/6. Predicting Systolic Blood Pressure from Age and Weight.vtt 5.0 kB
  • 2. 1-D Linear Regression Theory and Code/3. Coding the 1-D solution in Python.vtt 5.0 kB
  • 4. Practical machine learning issues/10. The Dummy Variable Trap.vtt 5.0 kB
  • 4. Practical machine learning issues/8. L2 Regularization - Theory.vtt 5.0 kB
  • 5. Conclusion and Next Steps/2. Exercises, practice, and how to get good at this.vtt 4.9 kB
  • 4. Practical machine learning issues/11. Gradient Descent Tutorial.vtt 4.9 kB
  • 3. Multiple linear regression and polynomial regression/4. Coding the multi-dimensional solution in Python.vtt 4.6 kB
  • 4. Practical machine learning issues/5. Categorical inputs.vtt 4.4 kB
  • 3. Multiple linear regression and polynomial regression/5. Polynomial regression - extending linear regression (with Python code).vtt 4.4 kB
  • 2. 1-D Linear Regression Theory and Code/5. Determine how good the model is - r-squared.vtt 4.2 kB
  • 1. Welcome/1. Welcome.vtt 4.1 kB
  • 4. Practical machine learning issues/16. L1 vs L2 Regularization.vtt 3.8 kB
  • 4. Practical machine learning issues/2. Interpreting the Weights.vtt 3.8 kB
  • 4. Practical machine learning issues/14. L1 Regularization - Theory.vtt 3.7 kB
  • 1. Welcome/6. How to Succeed in this Course.vtt 3.6 kB
  • 1. Welcome/4. Introduction to Moore's Law Problem.vtt 3.5 kB
  • 6. Appendix/1. What is the Appendix.vtt 3.4 kB
  • 4. Practical machine learning issues/13. Bypass the Dummy Variable Trap with Gradient Descent.vtt 3.1 kB
  • 4. Practical machine learning issues/15. L1 Regularization - Code.vtt 3.1 kB
  • 6. Appendix/2. BONUS Where to get Udemy coupons and FREE deep learning material.vtt 3.1 kB
  • 4. Practical machine learning issues/9. L2 Regularization - Code.vtt 3.0 kB
  • 4. Practical machine learning issues/12. Gradient Descent for Linear Regression.vtt 2.8 kB
  • 4. Practical machine learning issues/3. Generalization error, train and test sets.vtt 2.6 kB
  • 3. Multiple linear regression and polynomial regression/7. R-squared Quiz 2.vtt 2.4 kB
  • 4. Practical machine learning issues/6. One-Hot Encoding Quiz.vtt 2.3 kB
  • 2. 1-D Linear Regression Theory and Code/8. R-squared Quiz 1.vtt 2.0 kB
  • 3. Multiple linear regression and polynomial regression/3. How to solve multiple linear regression using only matrices.vtt 1.9 kB
  • 2. 1-D Linear Regression Theory and Code/6. R-squared in code.vtt 1.5 kB
  • 2. 1-D Linear Regression Theory and Code/4. Exercise Theory vs. Code.vtt 1.4 kB
  • 0. Websites you may like/1. (FreeTutorials.Us) Download Udemy Paid Courses For Free.url 328 Bytes
  • 0. Websites you may like/5. (Discuss.FTUForum.com) FTU Discussion Forum.url 294 Bytes
  • 0. Websites you may like/2. (FreeCoursesOnline.Me) Download Udacity, Masterclass, Lynda, PHLearn, Pluralsight Free.url 286 Bytes
  • 0. Websites you may like/4. (FTUApps.com) Download Cracked Developers Applications For Free.url 239 Bytes
  • 0. Websites you may like/How you can help Team-FTU.txt 237 Bytes
  • 0. Websites you may like/3. (NulledPremium.com) Download Cracked Website Themes, Plugins, Scripts And Stock Images.url 163 Bytes
  • 1. Welcome/5. What can linear regression be used for.html 143 Bytes

温馨提示

本站不存储任何资源内容，只收集BT种子元数据(例如文件名和文件大小)和磁力链接(BT种子标识符)，并提供查询服务，是一个完全合法的搜索引擎系统。网站不提供种子下载服务，用户可以通过第三方链接或磁力链接获取到相关的种子资源。本站也不对BT种子真实性及合法性负责，请用户注意甄别！