[Tutorialsplanet.NET] Udemy - Deep Learning Prerequisites Logistic Regression in Python

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[Tutorialsplanet.NET] Udemy - Deep Learning Prerequisites Logistic Regression in Python

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种子哈希：63a50f123bca253afa625672035aaea099dc9902
文件大小： 1.12G
已经下载：757次
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收录时间：2021-03-29
最近下载：2024-11-27

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文件列表

  • 8. Setting Up Your Environment/1. Windows-Focused Environment Setup 2018.mp4 195.3 MB
  • 9. Extra Help With Python Coding for Beginners/4. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
  • 3/2. Define the multi-dimensional problem and derive the solution.mp4 63.2 MB
  • 1. Start Here/3. Statistics vs. Machine Learning.mp4 58.4 MB
  • 8. Setting Up Your Environment/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
  • 10. Effective Learning Strategies for Machine Learning/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
  • 11. Appendix FAQ/2. BONUS Where to get discount coupons and FREE deep learning material.mp4 39.7 MB
  • 10. Effective Learning Strategies for Machine Learning/4. What order should I take your courses in (part 2).mp4 39.5 MB
  • 10. Effective Learning Strategies for Machine Learning/3. What order should I take your courses in (part 1).mp4 30.8 MB
  • 1. Start Here/2. How to Succeed in this Course.mp4 29.3 MB
  • 4. Practical concerns/8. The donut problem.mp4 25.9 MB
  • 2/2. Define the model in 1-D, derive the solution.mp4 25.9 MB
  • 9. Extra Help With Python Coding for Beginners/2. How to Code by Yourself (part 1).mp4 25.7 MB
  • 6. Project Facial Expression Recognition/5. Facial Expression Recognition in Code.mp4 25.2 MB
  • 4. Practical concerns/10. Why Divide by Square Root of D.mp4 24.6 MB
  • 7. Background Review/1. Gradient Descent Tutorial.mp4 23.9 MB
  • 6. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.mp4 22.5 MB
  • 2/9. Moore's Law Derivation.mp4 21.2 MB
  • 2/5. Determine how good the model is - r-squared.mp4 20.7 MB
  • 2/1. Define the model in 1-D, derive the solution (Updated Version).mp4 20.3 MB
  • 2/8. Demonstrating Moore's Law in Code.mp4 18.3 MB
  • 3/5. Polynomial regression - extending linear regression (with Python code).mp4 17.2 MB
  • 2/11. Suggestion Box.mp4 16.9 MB
  • 3/4. Coding the multi-dimensional solution in Python.mp4 15.6 MB
  • 9. Extra Help With Python Coding for Beginners/3. How to Code by Yourself (part 2).mp4 15.5 MB
  • 1. Start Here/5. Introduction to the E-Commerce Course Project.mp4 15.5 MB
  • 4. Practical concerns/3. L2 Regularization - Theory.mp4 15.4 MB
  • 3/1. Define the multi-dimensional problem and derive the solution (Updated Version).mp4 15.1 MB
  • 2/3. Coding the 1-D solution in Python.mp4 15.1 MB
  • 4. Practical concerns/9. The XOR problem.mp4 14.9 MB
  • 1. Start Here/1. Introduction and Outline.mp4 14.7 MB
  • 6. Project Facial Expression Recognition/4. Utilities walkthrough.mp4 14.1 MB
  • 10. Effective Learning Strategies for Machine Learning/1. How to Succeed in this Course (Long Version).mp4 13.6 MB
  • 3/6. Predicting Systolic Blood Pressure from Age and Weight.mp4 12.9 MB
  • 4. Practical concerns/6. L1 Regularization - Code.mp4 12.6 MB
  • 5. Checkpoint and applications How to make sure you know your stuff/1. BONUS Sentiment Analysis.mp4 12.0 MB
  • 6. Project Facial Expression Recognition/3. The class imbalance problem.mp4 10.6 MB
  • 6. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.mp4 10.3 MB
  • 9. Extra Help With Python Coding for Beginners/5. Python 2 vs Python 3.mp4 8.2 MB
  • 4. Practical concerns/2. Interpreting the Weights.mp4 6.6 MB
  • 11. Appendix FAQ/1. What is the Appendix.mp4 5.7 MB
  • 9. Extra Help With Python Coding for Beginners/1. How to Uncompress a .tar.gz file.mp4 5.7 MB
  • 5. Checkpoint and applications How to make sure you know your stuff/2. BONUS Exercises + how to get good at this.mp4 5.5 MB
  • 4. Practical concerns/7. L1 vs L2 Regularization.mp4 5.0 MB
  • 4. Practical concerns/1. Practical Section Introduction.mp4 5.0 MB
  • 2/6. R-squared in code.mp4 4.7 MB
  • 4. Practical concerns/4. L2 Regularization - Code.mp4 4.7 MB
  • 4. Practical concerns/5. L1 Regularization - Theory.mp4 4.6 MB
  • 2/7. Introduction to Moore's Law Problem.mp4 4.6 MB
  • 3/7. R-squared Quiz 2.mp4 3.7 MB
  • 4. Practical concerns/11. Practical Section Summary.mp4 3.6 MB
  • 3/3. How to solve multiple linear regression using only matrices.mp4 3.2 MB
  • 1. Start Here/4. Review of the classification problem.mp4 3.1 MB
  • 6. Project Facial Expression Recognition/6. Facial Expression Recognition Project Summary.mp4 3.1 MB
  • 2/10. R-squared Quiz 1.mp4 2.9 MB
  • 2/4. Exercise Theory vs. Code.mp4 1.1 MB
  • 10. Effective Learning Strategies for Machine Learning/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt 34.7 kB
  • 10. Effective Learning Strategies for Machine Learning/4. What order should I take your courses in (part 2).srt 25.7 kB
  • 9. Extra Help With Python Coding for Beginners/2. How to Code by Yourself (part 1).srt 24.9 kB
  • 8. Setting Up Your Environment/1. Windows-Focused Environment Setup 2018.srt 22.2 kB
  • 2/1. Define the model in 1-D, derive the solution (Updated Version).srt 18.1 kB
  • 10. Effective Learning Strategies for Machine Learning/3. What order should I take your courses in (part 1).srt 17.5 kB
  • 1. Start Here/3. Statistics vs. Machine Learning.srt 16.4 kB
  • 6. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.srt 16.4 kB
  • 10. Effective Learning Strategies for Machine Learning/1. How to Succeed in this Course (Long Version).srt 15.9 kB
  • 8. Setting Up Your Environment/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 15.8 kB
  • 9. Extra Help With Python Coding for Beginners/4. Proof that using Jupyter Notebook is the same as not using it.srt 15.4 kB
  • 9. Extra Help With Python Coding for Beginners/3. How to Code by Yourself (part 2).srt 14.4 kB
  • 1. Start Here/5. Introduction to the E-Commerce Course Project.srt 14.3 kB
  • 3/2. Define the multi-dimensional problem and derive the solution.srt 13.2 kB
  • 3/1. Define the multi-dimensional problem and derive the solution (Updated Version).srt 12.8 kB
  • 4. Practical concerns/3. L2 Regularization - Theory.srt 11.8 kB
  • 2/2. Define the model in 1-D, derive the solution.srt 11.3 kB
  • 4. Practical concerns/10. Why Divide by Square Root of D.srt 9.6 kB
  • 1. Start Here/2. How to Succeed in this Course.srt 9.5 kB
  • 11. Appendix FAQ/2. BONUS Where to get discount coupons and FREE deep learning material.srt 8.6 kB
  • 2/9. Moore's Law Derivation.srt 8.3 kB
  • 6. Project Facial Expression Recognition/5. Facial Expression Recognition in Code.srt 8.3 kB
  • 6. Project Facial Expression Recognition/3. The class imbalance problem.srt 8.1 kB
  • 4. Practical concerns/8. The donut problem.srt 7.5 kB
  • 2/8. Demonstrating Moore's Law in Code.srt 7.1 kB
  • 6. Project Facial Expression Recognition/1. Facial Expression Recognition Project Introduction.srt 7.1 kB
  • 9. Extra Help With Python Coding for Beginners/5. Python 2 vs Python 3.srt 6.8 kB
  • 5. Checkpoint and applications How to make sure you know your stuff/1. BONUS Sentiment Analysis.srt 6.6 kB
  • 4. Practical concerns/9. The XOR problem.srt 6.2 kB
  • 7. Background Review/1. Gradient Descent Tutorial.srt 6.1 kB
  • 2/3. Coding the 1-D solution in Python.srt 6.0 kB
  • 6. Project Facial Expression Recognition/4. Utilities walkthrough.srt 6.0 kB
  • 3/4. Coding the multi-dimensional solution in Python.srt 5.6 kB
  • 3/6. Predicting Systolic Blood Pressure from Age and Weight.srt 5.6 kB
  • 1. Start Here/1. Introduction and Outline.srt 5.4 kB
  • 3/5. Polynomial regression - extending linear regression (with Python code).srt 5.4 kB
  • 4. Practical concerns/2. Interpreting the Weights.srt 5.2 kB
  • 4. Practical concerns/6. L1 Regularization - Code.srt 5.1 kB
  • 2/11. Suggestion Box.srt 5.0 kB
  • 2/5. Determine how good the model is - r-squared.srt 4.8 kB
  • 4. Practical concerns/7. L1 vs L2 Regularization.srt 4.5 kB
  • 9. Extra Help With Python Coding for Beginners/1. How to Uncompress a .tar.gz file.srt 4.5 kB
  • 4. Practical concerns/5. L1 Regularization - Theory.srt 4.1 kB
  • 5. Checkpoint and applications How to make sure you know your stuff/2. BONUS Exercises + how to get good at this.srt 3.9 kB
  • 11. Appendix FAQ/1. What is the Appendix.srt 3.9 kB
  • 4. Practical concerns/1. Practical Section Introduction.srt 3.8 kB
  • 2/7. Introduction to Moore's Law Problem.srt 3.8 kB
  • 3/7. R-squared Quiz 2.srt 3.0 kB
  • 4. Practical concerns/11. Practical Section Summary.srt 2.8 kB
  • 1. Start Here/4. Review of the classification problem.srt 2.5 kB
  • 2/10. R-squared Quiz 1.srt 2.4 kB
  • 3/3. How to solve multiple linear regression using only matrices.srt 2.1 kB
  • 2/6. R-squared in code.srt 1.9 kB
  • 6. Project Facial Expression Recognition/6. Facial Expression Recognition Project Summary.srt 1.8 kB
  • 4. Practical concerns/4. L2 Regularization - Code.srt 1.7 kB
  • 2/4. Exercise Theory vs. Code.srt 1.7 kB
  • 1. Start Here/6. Easy first quiz.html 152 Bytes
  • [Tutorialsplanet.NET].url 128 Bytes

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