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【影视】 B&W Photography. Shoot Prerequisites

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00-03-Prerequisite-Exposure Essentials.mp4 485.1 MB
00-04-Prerequisite-Camera Gear.mp4 385.2 MB
00-05-Prerequisite-Lighting Essentials.mp4 278.8 MB
00-02-Prerequisite-Camera Settings.mp4 202.9 MB
00-01-Prerequisite-Introduction.mp4 32.6 MB

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【影视】 [FreeTutorials.Us] deep-learning-prerequisites-the-numpy-stack-in-python

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01 Introduction and Outline/quizzes/001 How will you practice what youve learned in this course.html 3.7 kB
01 Introduction and Outline/001 Whats this course about How can you succeed What should you know first.mp4 10.5 MB
01 Introduction and Outline/002 Where to get the code and how to install libraries.mp4 7.0 MB
02 Numpy/003 Lists vs. Arrays.mp4 12.4 MB
02 Numpy/004 Dot product 1 For loop vs. cosine method vs. dot function.mp4 9.2 MB
02 Numpy/005 Dot product 2 Speed comparison.mp4 2.9 MB
02 Numpy/006 Vectors and Matrices.mp4 6.7 MB
02 Numpy/007 Generating Matrices to Work With.mp4 8.3 MB
02 Numpy/008 Matrix Products.mp4 4.6 MB
02 Numpy/009 More Matrix Operations.mp4 13.2 MB
02 Numpy/010 Solving a Linear System.mp4 4.2 MB
02 Numpy/011 Word Problem.mp4 3.1 MB
03 Pandas/012 Manual Data Loading.mp4 9.5 MB
03 Pandas/013 DataFrames.mp4 7.5 MB
03 Pandas/014 More about DataFrames Selecting Rows and Columns.mp4 9.6 MB
03 Pandas/015 Even More about DataFrames Column Names.mp4 6.3 MB
03 Pandas/016 The apply Function.mp4 5.9 MB
03 Pandas/017 Joins.mp4 4.7 MB
04 Matplotlib/018 Line Chart.mp4 6.6 MB
04 Matplotlib/019 Scatterplot.mp4 7.4 MB

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【影视】 [UdemyCourseDownloader] Deep Learning Prerequisites Logistic Regression in Python

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07 Appendix/036 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp4 46.0 MB
udemycoursedownloader.com.url 132 Bytes
01 Start Here/001 Introduction and Outline.mp4 7.9 MB
01 Start Here/002 How to Succeed in this Course.mp4 9.2 MB
01 Start Here/003 Review of the classification problem.mp4 3.1 MB
01 Start Here/004 Introduction to the E-Commerce Course Project.mp4 15.5 MB
01 Start Here/quizzes/001 Easy first quiz.html 2.5 kB
02 Basics What is linear classification Whats the relation to neural networks/005 Linear Classification.mp4 7.9 MB
02 Basics What is linear classification Whats the relation to neural networks/006 Biological inspiration - the neuron.mp4 4.4 MB
02 Basics What is linear classification Whats the relation to neural networks/007 How do we calculate the output of a neuron logistic classifier - Theory.mp4 7.8 MB
02 Basics What is linear classification Whats the relation to neural networks/008 How do we calculate the output of a neuron logistic classifier - Code.mp4 6.1 MB
02 Basics What is linear classification Whats the relation to neural networks/009 E-Commerce Course Project Pre-Processing the Data.mp4 11.7 MB
02 Basics What is linear classification Whats the relation to neural networks/010 E-Commerce Course Project Making Predictions.mp4 6.0 MB
03 Solving for the optimal weights/011 A closed-form solution to the Bayes classifier.mp4 10.5 MB
03 Solving for the optimal weights/012 What do all these symbols mean X Y N D L J PY1X etc..mp4 6.7 MB
03 Solving for the optimal weights/013 The cross-entropy error function - Theory.mp4 4.7 MB
03 Solving for the optimal weights/014 The cross-entropy error function - Code.mp4 9.5 MB
03 Solving for the optimal weights/015 Visualizing the linear discriminant Bayes classifier Gaussian clouds.mp4 5.5 MB
03 Solving for the optimal weights/016 Maximizing the likelihood.mp4 13.3 MB
03 Solving for the optimal weights/017 Updating the weights using gradient descent - Theory.mp4 9.8 MB

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【影视】 [FreeCourseSite.com] Udemy - Deep Learning Prerequisites The Numpy Stack in Python (V2+)

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8. Setting Up Your Environment (FAQ by Student Request)/1. Windows-Focused Environment Setup 2018.mp4 195.3 MB
7. Machine Learning Basics/3. Classification in Code.mp4 131.5 MB
9. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
3. Matplotlib (New)/7. Where to Learn More Matplotlib.mp4 80.9 MB
2. Numpy (New)/7. Generating Data.mp4 66.2 MB
7. Machine Learning Basics/2. What is Classification.mp4 65.2 MB
7. Machine Learning Basics/5. Regression in Code.mp4 64.9 MB
1. Welcome and Logistics/1. Introduction and Outline.mp4 63.4 MB
2. Numpy (New)/5. Matrices.mp4 60.0 MB
2. Numpy (New)/2. Arrays vs Lists.mp4 53.2 MB
4. Pandas (New)/3. Selecting Rows and Columns.mp4 51.5 MB
7. Machine Learning Basics/9. Comparing Different Machine Learning Models.mp4 47.7 MB
8. Setting Up Your Environment (FAQ by Student Request)/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
7. Machine Learning Basics/4. What is Regression.mp4 45.3 MB
5. Scipy (New)/5. Where to Learn More Scipy.mp4 40.8 MB
7. Machine Learning Basics/1. Machine Learning Section Introduction.mp4 40.8 MB
2. Numpy (New)/9. Where to Learn More Numpy.mp4 40.7 MB
3. Matplotlib (New)/5. Plotting Images.mp4 40.5 MB
11. Appendix FAQ Finale/1. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 39.7 MB
10. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 39.4 MB

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8. Setting Up Your Environment (FAQ by Student Request)/1. Windows-Focused Environment Setup 2018.mp4 195.3 MB
7. Machine Learning Basics/3. Classification in Code.mp4 131.5 MB
9. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
3. Matplotlib (New)/7. Where to Learn More Matplotlib.mp4 80.9 MB
2. Numpy (New)/7. Generating Data.mp4 66.2 MB
7. Machine Learning Basics/2. What is Classification.mp4 65.2 MB
7. Machine Learning Basics/5. Regression in Code.mp4 64.9 MB
1. Welcome and Logistics/1. Introduction and Outline.mp4 63.4 MB
2. Numpy (New)/5. Matrices.mp4 60.0 MB
2. Numpy (New)/2. Arrays vs Lists.mp4 53.2 MB
4. Pandas (New)/3. Selecting Rows and Columns.mp4 51.5 MB
7. Machine Learning Basics/9. Comparing Different Machine Learning Models.mp4 47.7 MB
8. Setting Up Your Environment (FAQ by Student Request)/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
7. Machine Learning Basics/4. What is Regression.mp4 45.3 MB
5. Scipy (New)/5. Where to Learn More Scipy.mp4 40.8 MB
7. Machine Learning Basics/1. Machine Learning Section Introduction.mp4 40.8 MB
2. Numpy (New)/9. Where to Learn More Numpy.mp4 40.7 MB
3. Matplotlib (New)/5. Plotting Images.mp4 40.5 MB
11. Appendix FAQ Finale/1. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 39.7 MB
10. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 39.4 MB

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6. Appendix FAQ/3. Windows-Focused Environment Setup 2018.mp4 195.3 MB
6. Appendix FAQ/6. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
2. Numpy (New)/7. Generating Data.mp4 66.2 MB
1. Welcome and Logistics/1. Introduction and Outline.mp4 63.4 MB
2. Numpy (New)/5. Matrices.mp4 60.0 MB
2. Numpy (New)/2. Arrays vs Lists.mp4 53.2 MB
4. Pandas (New)/3. Selecting Rows and Columns.mp4 51.5 MB
6. Appendix FAQ/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
3. Matplotlib (New)/5. Plotting Images.mp4 40.5 MB
6. Appendix FAQ/9. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 39.7 MB
6. Appendix FAQ/8. What order should I take your courses in (part 2).mp4 39.4 MB
6. Appendix FAQ/2. Bonus Section on Machine Learning Basics.mp4 36.7 MB
6. Appendix FAQ/7. What order should I take your courses in (part 1).mp4 30.8 MB
2. Numpy (New)/3. Dot Product.mp4 27.6 MB
1. Welcome and Logistics/5. Extra Resources.mp4 26.5 MB
2. Numpy (New)/1. Numpy Section Introduction.mp4 25.2 MB
4. Pandas (New)/2. Loading in Data.mp4 24.8 MB
5. Scipy (New)/3. Convolution.mp4 22.5 MB
6. Appendix FAQ/5. Python 2 vs Python 3.mp4 20.0 MB
3. Matplotlib (New)/3. Scatterplot.mp4 18.8 MB

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[TutsNode.com] - Deep Learning Prerequisites/08 Setting Up Your Environment (FAQ by Student Request)/044 Windows-Focused Environment Setup 2018.mp4 195.3 MB
[TutsNode.com] - Deep Learning Prerequisites/07 Machine Learning Basics/035 Classification in Code.mp4 131.5 MB
[TutsNode.com] - Deep Learning Prerequisites/09 Extra Help With Python Coding for Beginners (FAQ by Student Request)/047 Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
[TutsNode.com] - Deep Learning Prerequisites/03 Matplotlib (New)/019 Where to Learn More Matplotlib.mp4 80.9 MB
[TutsNode.com] - Deep Learning Prerequisites/02 Numpy (New)/009 Generating Data.mp4 66.2 MB
[TutsNode.com] - Deep Learning Prerequisites/07 Machine Learning Basics/034 What is Classification_.mp4 65.2 MB
[TutsNode.com] - Deep Learning Prerequisites/07 Machine Learning Basics/037 Regression in Code.mp4 64.9 MB
[TutsNode.com] - Deep Learning Prerequisites/01 Welcome and Logistics/001 Introduction and Outline.mp4 63.4 MB
[TutsNode.com] - Deep Learning Prerequisites/02 Numpy (New)/007 Matrices.mp4 60.0 MB
[TutsNode.com] - Deep Learning Prerequisites/02 Numpy (New)/004 Arrays vs Lists.mp4 53.2 MB
[TutsNode.com] - Deep Learning Prerequisites/04 Pandas (New)/022 Selecting Rows and Columns.mp4 51.5 MB
[TutsNode.com] - Deep Learning Prerequisites/07 Machine Learning Basics/041 Comparing Different Machine Learning Models.mp4 47.7 MB
[TutsNode.com] - Deep Learning Prerequisites/08 Setting Up Your Environment (FAQ by Student Request)/045 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.0 MB
[TutsNode.com] - Deep Learning Prerequisites/07 Machine Learning Basics/036 What is Regression_.mp4 45.3 MB
[TutsNode.com] - Deep Learning Prerequisites/05 Scipy (New)/031 Where to Learn More Scipy.mp4 40.8 MB
[TutsNode.com] - Deep Learning Prerequisites/07 Machine Learning Basics/033 Machine Learning_ Section Introduction.mp4 40.8 MB
[TutsNode.com] - Deep Learning Prerequisites/02 Numpy (New)/011 Where to Learn More Numpy.mp4 40.7 MB
[TutsNode.com] - Deep Learning Prerequisites/03 Matplotlib (New)/017 Plotting Images.mp4 40.5 MB
[TutsNode.com] - Deep Learning Prerequisites/11 Appendix _ FAQ Finale/050 BONUS_ Where to get Udemy coupons and FREE deep learning material.mp4 39.7 MB
[TutsNode.com] - Deep Learning Prerequisites/10 Effective Learning Strategies for Machine Learning (FAQ by Student Request)/049 Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 39.4 MB

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【影视】 [FreeCourseSite.com] Udemy - Deep Learning Prerequisites The Numpy Stack in Python (V2+)

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8. Setting Up Your Environment (FAQ by Student Request)/1. Windows-Focused Environment Setup 2018.mp4 195.3 MB
7. Machine Learning Basics/3. Classification in Code.mp4 131.5 MB
9. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
3. Matplotlib (New)/7. Where to Learn More Matplotlib.mp4 80.9 MB
2. Numpy (New)/7. Generating Data.mp4 66.2 MB
7. Machine Learning Basics/2. What is Classification.mp4 65.2 MB
7. Machine Learning Basics/5. Regression in Code.mp4 64.9 MB
1. Welcome and Logistics/1. Introduction and Outline.mp4 63.4 MB
2. Numpy (New)/5. Matrices.mp4 60.0 MB
2. Numpy (New)/2. Arrays vs Lists.mp4 53.2 MB
4. Pandas (New)/3. Selecting Rows and Columns.mp4 51.5 MB
7. Machine Learning Basics/9. Comparing Different Machine Learning Models.mp4 47.7 MB
8. Setting Up Your Environment (FAQ by Student Request)/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
7. Machine Learning Basics/4. What is Regression.mp4 45.3 MB
5. Scipy (New)/5. Where to Learn More Scipy.mp4 40.8 MB
7. Machine Learning Basics/1. Machine Learning Section Introduction.mp4 40.8 MB
2. Numpy (New)/9. Where to Learn More Numpy.mp4 40.7 MB
3. Matplotlib (New)/5. Plotting Images.mp4 40.5 MB
11. Appendix FAQ Finale/1. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 39.7 MB
10. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 39.4 MB

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6. Appendix FAQ/3. Windows-Focused Environment Setup 2018.mp4 195.3 MB
6. Appendix FAQ/6. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
2. Numpy (New)/7. Generating Data.mp4 66.2 MB
1. Welcome and Logistics/1. Introduction and Outline.mp4 63.4 MB
2. Numpy (New)/5. Matrices.mp4 60.0 MB
2. Numpy (New)/2. Arrays vs Lists.mp4 53.2 MB
4. Pandas (New)/3. Selecting Rows and Columns.mp4 51.5 MB
6. Appendix FAQ/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
3. Matplotlib (New)/5. Plotting Images.mp4 40.5 MB
6. Appendix FAQ/9. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 39.7 MB
6. Appendix FAQ/8. What order should I take your courses in (part 2).mp4 39.4 MB
6. Appendix FAQ/2. Bonus Section on Machine Learning Basics.mp4 36.7 MB
6. Appendix FAQ/7. What order should I take your courses in (part 1).mp4 30.8 MB
2. Numpy (New)/3. Dot Product.mp4 27.6 MB
1. Welcome and Logistics/5. Extra Resources.mp4 26.5 MB
2. Numpy (New)/1. Numpy Section Introduction.mp4 25.2 MB
4. Pandas (New)/2. Loading in Data.mp4 24.8 MB
5. Scipy (New)/3. Convolution.mp4 22.5 MB
6. Appendix FAQ/5. Python 2 vs Python 3.mp4 20.0 MB
3. Matplotlib (New)/3. Scatterplot.mp4 18.8 MB

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【影视】 [FreeCourseLab.com] Udemy - Deep Learning Prerequisites Linear Regression in Python

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6. Appendix/3. Windows-Focused Environment Setup 2018.mp4 195.3 MB
6. Appendix/9. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
1. Welcome/1. Welcome.mp4 52.1 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
6. Appendix/11. What order should I take your courses in (part 2).mp4 39.4 MB
3. Multiple linear regression and polynomial regression/2. Define the multi-dimensional problem and derive the solution.mp4 37.8 MB
6. Appendix/10. What order should I take your courses in (part 1).mp4 30.7 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
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

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

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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

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6. Setting Up Your Environment (FAQ by Student Request)/1. Windows-Focused Environment Setup 2018.mp4 195.3 MB
1. Welcome/4. Anyone Can Succeed in this Course.mp4 88.1 MB
7. Extra Help With Python Coding for Beginners (FAQ by Student Request)/3. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
1. Welcome/5. Statistics vs. Machine Learning.mp4 58.2 MB
1. Welcome/1. Welcome.mp4 52.1 MB
6. Setting Up Your Environment (FAQ by Student Request)/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
8/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.8 MB
9. Appendix FAQ Finale/2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 39.7 MB
8/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 39.4 MB
3. Multiple linear regression and polynomial regression/2. Define the multi-dimensional problem and derive the solution.mp4 37.8 MB
8/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 30.7 MB
2. 1-D Linear Regression Theory and Code/2. Define the model in 1-D, derive the solution.mp4 25.9 MB
7. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. How to Code by Yourself (part 1).mp4 25.7 MB
4. Practical machine learning issues/17. Why Divide by Square Root of D.mp4 24.6 MB
4. Practical machine learning issues/11. Gradient Descent Tutorial.mp4 23.9 MB
2. 1-D Linear Regression Theory and Code/9. Moore's Law Derivation.mp4 21.2 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
8/1. How to Succeed in this Course (Long Version).mp4 19.2 MB
2. 1-D Linear Regression Theory and Code/8. Demonstrating Moore's Law in Code.mp4 18.4 MB
4. Practical machine learning issues/4. Generalization and Overfitting Demonstration in Code.mp4 18.1 MB

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【影视】 c.suite setup 4.5.6 with prerequisites

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c.suite Video/2. Разработка стратегии управления в модуле c.Strategy.mp4 499.3 MB
Prerequisites_setup.exe 397.8 MB
c.suite Video/3. Разработка пользовательского интерфейса в модуле c.Mask.mp4 255.7 MB
Carel c.strategy_4.5.6.exe 122.2 MB
c.touch 2.9.0.601 installer.exe 115.1 MB
c.web_2.5.9_setup.exe 88.2 MB
c.suite Video/4. Конфигурирование внешних связей контроллера в модуле c.Design.mp4 75.7 MB
Carel c.factory_4.5.6.exe 50.3 MB
Carel c.mask_4.5.6.exe 31.8 MB
Carel c.design_4.5.6.exe 28.4 MB
c.suite Video/31-Overview_LD_SFC_languages.mp4 26.8 MB
c.suite Video/1. Введение Общая информация о среде разработки c.Suite.mp4 15.7 MB
Carel Virtual pCO_4.5.6.exe 1.2 MB
c.suite Video/1tool-c.suite tips_and_tricks.pdf 1.0 MB
Libraries_setup.exe 886.2 kB
Setup.exe 295.4 kB
c.suite Video/DeviceCreator1.PNG 111.4 kB
c.suite Video/DeviceCreator2.PNG 87.9 kB

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7. Appendix FAQ/3. Windows-Focused Environment Setup 2018.mp4 195.3 MB
2. Basics What is linear classification What's the relation to neural networks/3. How do we calculate the output of a neuron logistic classifier - Theory.srt 84.1 MB
7. Appendix FAQ/10. Proof that using Jupyter Notebook is the same as not using it.srt 82.1 MB
7. Appendix FAQ/10. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
4. Practical concerns/11. Practical Section Summary.srt 82.1 MB
1. Start Here/1. Introduction and Outline.mp4 49.2 MB
7. Appendix FAQ/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
7. Appendix FAQ/9. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
7. Appendix FAQ/14. BONUS Where to get discount coupons and FREE deep learning material.mp4 39.7 MB
7. Appendix FAQ/13. What order should I take your courses in (part 2).mp4 39.4 MB
7. Appendix FAQ/12. What order should I take your courses in (part 1).mp4 30.7 MB
2. Basics What is linear classification What's the relation to neural networks/5. Interpretation of Logistic Regression Output.mp4 29.2 MB
3. Solving for the optimal weights/7. Maximizing the likelihood.mp4 26.4 MB
4. Practical concerns/8. The donut problem.mp4 25.9 MB
7. Appendix FAQ/5. 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. Appendix FAQ/2. Gradient Descent Tutorial.mp4 23.9 MB
6. Project Facial Expression Recognition/2. Facial Expression Recognition Problem Description.mp4 22.5 MB
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6. Setting Up Your Environment/1. Windows-Focused Environment Setup 2018.mp4 195.3 MB
7. Extra Help With Python Coding for Beginners/3. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
3. Multiple linear regression and polynomial regression/2. Define the multi-dimensional problem and derive the solution.mp4 63.2 MB
1. Welcome/5. Statistics vs. Machine Learning.mp4 58.2 MB
1. Welcome/1. Welcome.mp4 52.1 MB
6. Setting Up Your Environment/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.0 MB
8. Effective Learning Strategies for Machine Learning/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
9. Appendix FAQ/2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 39.7 MB
8. Effective Learning Strategies for Machine Learning/4. What order should I take your courses in (part 2).mp4 39.5 MB
8. Effective Learning Strategies for Machine Learning/3. What order should I take your courses in (part 1).mp4 30.7 MB
1. Welcome/4. How to Succeed in this Course.mp4 29.3 MB
2. 1-D Linear Regression Theory and Code/2. Define the model in 1-D, derive the solution.mp4 25.9 MB
7. Extra Help With Python Coding for Beginners/1. How to Code by Yourself (part 1).mp4 25.7 MB
4. Practical machine learning issues/17. Why Divide by Square Root of D.mp4 24.6 MB
4. Practical machine learning issues/11. Gradient Descent Tutorial.mp4 23.9 MB
2. 1-D Linear Regression Theory and Code/9. Moore's Law Derivation.mp4 21.2 MB
2. 1-D Linear Regression Theory and Code/5. Determine how good the model is - r-squared.mp4 20.7 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
8. Effective Learning Strategies for Machine Learning/1. How to Succeed in this Course (Long Version).mp4 19.2 MB
2. 1-D Linear Regression Theory and Code/8. Demonstrating Moore's Law in Code.mp4 18.3 MB

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8/1. Anaconda Environment Setup.mp4 195.3 MB
9. Extra Help With Python Coding for Beginners (FAQ by Student Request)/4. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
1. Start Here/3. Statistics vs. Machine Learning.mp4 58.4 MB
8/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.0 MB
1. Start Here/2. How to Succeed in this Course.mp4 45.9 MB
1. Start Here/1. Introduction and Outline.mp4 41.3 MB
10/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
11. Appendix FAQ Finale/2. BONUS.srt 39.7 MB
11. Appendix FAQ Finale/2. BONUS.mp4 39.7 MB
10/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 39.4 MB
10/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 30.7 MB
2/5. Interpretation of Logistic Regression Output.mp4 29.3 MB
3. Solving for the optimal weights/7. Maximizing the likelihood.mp4 26.4 MB
4. Practical concerns/8. The donut problem.mp4 25.9 MB
9. Extra Help With Python Coding for Beginners (FAQ by Student Request)/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
3. Solving for the optimal weights/10. E-Commerce Course Project Training the Logistic Model.mp4 17.9 MB

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6. Setting Up Your Environment (FAQ by Student Request)/1. Anaconda Environment Setup.mp4 195.3 MB
7. Extra Help With Python Coding for Beginners (FAQ by Student Request)/3. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
1. Welcome/3. Statistics vs. Machine Learning.mp4 58.2 MB
6. Setting Up Your Environment (FAQ by Student Request)/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.0 MB
1. Welcome/2. How to Succeed in this Course.mp4 46.0 MB
1. Welcome/1. Introduction and Outline.mp4 44.8 MB
8/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.8 MB
9. Appendix FAQ Finale/2. BONUS.mp4 39.7 MB
8/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 39.4 MB
3. Multiple linear regression and polynomial regression/2. Define the multi-dimensional problem and derive the solution.mp4 37.8 MB
8/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 30.7 MB
2. 1-D Linear Regression Theory and Code/4. Define the model in 1-D, derive the solution.mp4 25.9 MB
7. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. How to Code by Yourself (part 1).mp4 25.7 MB
4. Practical machine learning issues/17. Why Divide by Square Root of D.mp4 24.6 MB
4. Practical machine learning issues/11. Gradient Descent Tutorial.mp4 23.9 MB
2. 1-D Linear Regression Theory and Code/11. Moore's Law Derivation.mp4 21.2 MB
2. 1-D Linear Regression Theory and Code/3. Define the model in 1-D, derive the solution (Updated Version).mp4 20.3 MB
8/1. How to Succeed in this Course (Long Version).mp4 19.2 MB
2. 1-D Linear Regression Theory and Code/10. 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

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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

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6. Appendix FAQ/3. Windows-Focused Environment Setup 2018.mp4 195.3 MB
6. Appendix FAQ/6. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
6. Appendix FAQ/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
6. Appendix FAQ/8. What order should I take your courses in (part 2).mp4 39.4 MB
6. Appendix FAQ/2. Bonus Section on Machine Learning Basics.mp4 36.7 MB
3. Pandas/7. .values vs .as_matrix().mp4 34.9 MB
6. Appendix FAQ/7. What order should I take your courses in (part 1).mp4 30.7 MB
6. Appendix FAQ/5. Python 2 vs Python 3.mp4 20.0 MB
6. Appendix FAQ/1. Exercises.mp4 17.5 MB
4. Matplotlib/4. Plotting Images.mp4 12.8 MB
2. Numpy/7. More Matrix Operations.mp4 12.6 MB
2. Numpy/1. Lists vs. Arrays.mp4 11.2 MB
1. Introduction and Outline/1. What’s this course about How can you succeed What should you know first.mp4 10.6 MB
5. Scipy/5. Other Interesting Scipy Functions.mp4 10.5 MB
5. Scipy/1. Gaussian PDF and CDF.mp4 8.9 MB
3. Pandas/3. More about DataFrames Selecting Rows and Columns.mp4 8.6 MB
2. Numpy/2. Dot product 1 For loop vs. cosine method vs. dot function.mp4 8.6 MB
3. Pandas/1. Manual Data Loading.mp4 8.5 MB
1. Introduction and Outline/2. Where to get the code (and how to install libraries).mp4 7.9 MB
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6. Appendix FAQ/3. Windows-Focused Environment Setup 2018.mp4 195.3 MB
6. Appendix FAQ/6. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
2. Numpy (New)/7. Generating Data.mp4 66.3 MB
1. Welcome and Logistics/1. Introduction and Outline.mp4 63.4 MB
2. Numpy (New)/5. Matrices.mp4 60.0 MB
2. Numpy (New)/2. Arrays vs Lists.mp4 53.2 MB
4. Pandas (New)/3. Selecting Rows and Columns.mp4 51.5 MB
6. Appendix FAQ/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
3. Matplotlib (New)/5. Plotting Images.mp4 40.5 MB
6. Appendix FAQ/9. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 39.7 MB
6. Appendix FAQ/8. What order should I take your courses in (part 2).mp4 39.5 MB
6. Appendix FAQ/2. Bonus Section on Machine Learning Basics.mp4 36.7 MB
6. Appendix FAQ/7. What order should I take your courses in (part 1).mp4 30.8 MB
2. Numpy (New)/3. Dot Product.mp4 27.6 MB
1. Welcome and Logistics/5. Extra Resources.mp4 26.5 MB
2. Numpy (New)/1. Numpy Section Introduction.mp4 25.2 MB
4. Pandas (New)/2. Loading in Data.mp4 24.8 MB
5. Scipy (New)/3. Convolution.mp4 22.5 MB
6. Appendix FAQ/5. Python 2 vs Python 3.mp4 20.0 MB
3. Matplotlib (New)/3. Scatterplot.mp4 18.8 MB

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