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

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9 - Setting Up Your Environment FAQ by Student Request/45 - Anaconda Environment Setup.mp4 323.3 MB
8 - Machine Learning Basics/36 - Classification in Code.mp4 217.9 MB
9 - Setting Up Your Environment FAQ by Student Request/46 - How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp4 200.7 MB
11 - Effective Learning Strategies for Machine Learning FAQ by Student Request/50 - Machine Learning and AI Prerequisite Roadmap pt 2.mp4 142.4 MB
11 - Effective Learning Strategies for Machine Learning FAQ by Student Request/49 - Machine Learning and AI Prerequisite Roadmap pt 1.mp4 141.0 MB
7 - Beginner Troubleshooting/33 - What if I dont meet the math prerequisites.mp4 121.2 MB
10 - Extra Help With Python Coding for Beginners FAQ by Student Request/48 - Proof that using Jupyter Notebook is the same as not using it.mp4 113.3 MB
2 - Numpy New/9 - Generating Data.mp4 90.7 MB
8 - Machine Learning Basics/38 - Regression in Code.mp4 81.0 MB
8 - Machine Learning Basics/35 - What is Classification.mp4 76.3 MB
12 - Appendix FAQ Finale/51 - BONUS.mp4 63.8 MB
1 - Welcome and Logistics/1 - Introduction and Outline.mp4 63.4 MB
2 - Numpy New/4 - Arrays vs Lists.mp4 45.4 MB
3 - Matplotlib New/19 - Where to Learn More Matplotlib.mp4 44.3 MB
2 - Numpy New/12 - Suggestion Box.mp4 41.6 MB
8 - Machine Learning Basics/39 - What is a Feature Vector.mp4 40.4 MB
8 - Machine Learning Basics/42 - Comparing Different Machine Learning Models.mp4 40.4 MB
2 - Numpy New/7 - Matrices.mp4 36.5 MB
8 - Machine Learning Basics/37 - What is Regression.mp4 36.4 MB
8 - Machine Learning Basics/34 - Machine Learning Section Introduction.mp4 35.7 MB

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【压缩文件】 microsoft-visual-studio-.-net-2003-prerequisites

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Microsoft Visual Studio .NET 2003 Prerequisites.iso 169.7 MB
vs2k3-prq.jpg 413.3 kB
microsoft-visual-studio-.-net-2003-prerequisites_meta.sqlite 20.5 kB
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microsoft-visual-studio-.-net-2003-prerequisites_meta.xml 907 Bytes

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【影视】 Data Science Prerequisites - Numpy, Matplotlib, and Pandas in Python

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Chapter 6 Machine Learning Basics/003. Classification in Code.mp4 84.9 MB
Chapter 3 Matplotlib/007. Where to Learn More Matplotlib.mp4 55.8 MB
Chapter 6 Machine Learning Basics/002. What Is Classification.mp4 52.2 MB
Chapter 2 NumPy/007. Generating Data.mp4 50.1 MB
Chapter 1 Welcome and Logistics/001. Introduction and Outline.mp4 45.3 MB
Chapter 2 NumPy/005. Matrices.mp4 44.8 MB
Chapter 6 Machine Learning Basics/005. Regression in Code.mp4 43.5 MB
Chapter 6 Machine Learning Basics/009. Comparing Different Machine Learning Models.mp4 39.9 MB
Chapter 2 NumPy/002. Arrays Versus Lists.mp4 39.8 MB
Chapter 6 Machine Learning Basics/004. What Is Regression.mp4 39.7 MB
Chapter 4 Pandas/003. Selecting Rows and Columns.mp4 35.6 MB
Chapter 6 Machine Learning Basics/001. Machine Learning Section Introduction.mp4 35.2 MB
Chapter 6 Machine Learning Basics/010. Machine Learning and Deep Learning Future Topics.mp4 32.7 MB
Chapter 2 NumPy/009. Where to Learn More NumPy.mp4 32.7 MB
Chapter 5 SciPy/005. Where to Learn More SciPy.mp4 29.7 MB
Chapter 3 Matplotlib/005. Plotting Images.mp4 29.1 MB
Chapter 6 Machine Learning Basics/006. What Is a Feature Vector.mp4 29.0 MB
Chapter 2 NumPy/003. Dot Product.mp4 22.4 MB
Chapter 6 Machine Learning Basics/011. Machine Learning Section Summary.mp4 21.3 MB
Chapter 4 Pandas/007. Where to Learn More Pandas.mp4 21.3 MB

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【影视】 [Udemy] Deep Learning Prerequisites The Numpy Stack in Python (V2+) (2020) [En]

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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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【压缩文件】 Deep Learning Prerequisites Logistic Regression in Python

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Deep Learning Prerequisites Logistic Regression in Python.zip 774.8 MB
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【影视】 [ DevCourseWeb.com ] Udemy - Prerequisites to Machine Learning - A Beginners Guide

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~Get Your Files Here !/2. Python for Machine Learning/3. Range, Lists and Tuples.mp4 80.6 MB
~Get Your Files Here !/2. Python for Machine Learning/2. Functions.mp4 61.9 MB
~Get Your Files Here !/3. Packages and Statistics for Machine Learning/6. Mean, Median and Mode.mp4 43.6 MB
~Get Your Files Here !/3. Packages and Statistics for Machine Learning/5. Matplotlib Continue....mp4 42.3 MB
~Get Your Files Here !/3. Packages and Statistics for Machine Learning/7. Variance and Standard Deviation.mp4 40.1 MB
~Get Your Files Here !/3. Packages and Statistics for Machine Learning/1. NumPy.mp4 39.1 MB
~Get Your Files Here !/3. Packages and Statistics for Machine Learning/4. Matplotlib.mp4 36.4 MB
~Get Your Files Here !/2. Python for Machine Learning/4. Importing Modules.mp4 32.0 MB
~Get Your Files Here !/3. Packages and Statistics for Machine Learning/3. Read CSV File.mp4 31.9 MB
~Get Your Files Here !/2. Python for Machine Learning/1. Print Statement and Variables.mp4 27.2 MB
~Get Your Files Here !/3. Packages and Statistics for Machine Learning/2. Pandas.mp4 26.2 MB
~Get Your Files Here !/1. Introduction/4. Google Colab Notebook.mp4 23.6 MB
~Get Your Files Here !/1. Introduction/3. Introduction to Machine Learning.mp4 15.3 MB
~Get Your Files Here !/1. Introduction/1. Course Overview.mp4 6.7 MB
~Get Your Files Here !/3. Packages and Statistics for Machine Learning/5.1 matplotlib.ipynb 44.2 kB
~Get Your Files Here !/2. Python for Machine Learning/3. Range, Lists and Tuples.srt 21.8 kB
~Get Your Files Here !/3. Packages and Statistics for Machine Learning/6. Mean, Median and Mode.srt 11.6 kB
~Get Your Files Here !/3. Packages and Statistics for Machine Learning/5. Matplotlib Continue....srt 10.3 kB
~Get Your Files Here !/3. Packages and Statistics for Machine Learning/7. Variance and Standard Deviation.srt 10.2 kB
~Get Your Files Here !/2. Python for Machine Learning/1. Print Statement and Variables.srt 9.4 kB

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

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6. Appendix FAQ/3. Windows-Focused Environment Setup 2018.mp4 195.3 MB
6. Appendix FAQ/9. 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
6. Appendix FAQ/2. BONUS Where to get Udemy coupons and FREE deep learning material.srt 62.3 MB
1. Welcome/1. Welcome.mp4 52.1 MB
6. Appendix FAQ/11. What order should I take your courses in (part 2).srt 49.7 MB
6. Appendix FAQ/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
4. Practical machine learning issues/3. Generalization error, train and test sets.srt 40.9 MB
6. Appendix FAQ/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
6. Appendix FAQ/2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 39.7 MB
6. Appendix FAQ/11. What order should I take your courses in (part 2).mp4 39.4 MB
6. Appendix FAQ/10. What order should I take your courses in (part 1).srt 30.8 MB
6. Appendix FAQ/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 FAQ/5. 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/5. Determine how good the model is - r-squared.mp4 20.7 MB
6. Appendix FAQ/6. How to Code by Yourself (part 2).srt 20.5 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

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【影视】 [ DevCourseWeb.com ] Udemy - Az-104 - Prerequisites For Azure Administrators

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~Get Your Files Here !/3 - Configure Azure resources with tools/7 - Interactive lab Azure PowerShell.mp4 72.6 MB
~Get Your Files Here !/3 - Configure Azure resources with tools/9 - Interactive lab Azure CLI.mp4 69.0 MB
~Get Your Files Here !/8 - Deploy Azure infrastructure by using JSON ARM templates/44 - Explore Azure Resource Manager template structure.mp4 61.3 MB
~Get Your Files Here !/6 - Automate Azure tasks using scripts with PowerShell/32 - Create an Azure Resource using scripts in Azure PowerShell.mp4 56.3 MB
~Get Your Files Here !/3 - Configure Azure resources with tools/5 - Use Azure Cloud Shell.mp4 54.9 MB
~Get Your Files Here !/8 - Deploy Azure infrastructure by using JSON ARM templates/46 - Add flexibility to your ARM template by using parameters and outputs.mp4 53.3 MB
~Get Your Files Here !/5 - Configure resources with Azure Resource Manager templates/26 - Interactive lab simulation templates.mp4 44.7 MB
~Get Your Files Here !/6 - Automate Azure tasks using scripts with PowerShell/29 - Decide if Azure PowerShell is right for your tasks.mp4 44.5 MB
~Get Your Files Here !/3 - Configure Azure resources with tools/6 - Use Azure PowerShell.mp4 35.0 MB
~Get Your Files Here !/6 - Automate Azure tasks using scripts with PowerShell/34 - Create and save scripts in Azure PowerShell.mp4 30.9 MB
~Get Your Files Here !/7 - Control Azure services with the CLI/40 - Work with the Azure CLI.mp4 28.0 MB
~Get Your Files Here !/3 - Configure Azure resources with tools/8 - Use Azure CLI.mp4 22.5 MB
~Get Your Files Here !/4 - Use Azure Resource Manager/15 - Create Azure Resource Manager locks.mp4 21.2 MB
~Get Your Files Here !/4 - Use Azure Resource Manager/12 - Review Azure Resource Manager benefits.mp4 21.0 MB
~Get Your Files Here !/5 - Configure resources with Azure Resource Manager templates/21 - Review Azure Resource Manager template advantages.mp4 19.9 MB
~Get Your Files Here !/4 - Use Azure Resource Manager/14 - Create resource groups.mp4 17.6 MB
~Get Your Files Here !/4 - Use Azure Resource Manager/13 - Review Azure resource terminology.mp4 16.6 MB
~Get Your Files Here !/5 - Configure resources with Azure Resource Manager templates/24 - Consider Bicep templates.mp4 16.3 MB
~Get Your Files Here !/5 - Configure resources with Azure Resource Manager templates/22 - Explore the Azure Resource Manager template schema.mp4 15.1 MB
~Get Your Files Here !/7 - Control Azure services with the CLI/38 - What is the Azure CLI.mp4 13.3 MB

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【影视】 tutsgalaxy.-com-udemy-deep-learning-prerequisites-linear-regression-in-python

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6. Appendix FAQ/3. Windows-Focused Environment Setup 2018.mp4 195.3 MB
6. Appendix FAQ/9. 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
6. Appendix FAQ/2. BONUS Where to get Udemy coupons and FREE deep learning material.srt 62.3 MB
1. Welcome/1. Welcome.mp4 52.1 MB
6. Appendix FAQ/11. What order should I take your courses in (part 2).srt 49.7 MB
6. Appendix FAQ/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
6. Appendix FAQ/8. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.9 MB
4. Practical machine learning issues/3. Generalization error, train and test sets.srt 40.9 MB
6. Appendix FAQ/2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 39.7 MB
6. Appendix FAQ/11. What order should I take your courses in (part 2).mp4 39.4 MB
6. Appendix FAQ/10. What order should I take your courses in (part 1).srt 30.8 MB
6. Appendix FAQ/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 FAQ/5. 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/5. Determine how good the model is - r-squared.mp4 20.7 MB
6. Appendix FAQ/6. How to Code by Yourself (part 2).srt 20.5 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

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【影视】 [GigaCourse.Com] Udemy - Deep Learning Prerequisites The Numpy Stack in Python V2

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9 - Setting Up Your Environment FAQ by Student Request/45 - Anaconda Environment Setup.mp4 323.3 MB
8 - Machine Learning Basics/36 - Classification in Code.mp4 217.9 MB
9 - Setting Up Your Environment FAQ by Student Request/46 - How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp4 200.7 MB
11 - Effective Learning Strategies for Machine Learning FAQ by Student Request/50 - Machine Learning and AI Prerequisite Roadmap pt 2.mp4 142.4 MB
11 - Effective Learning Strategies for Machine Learning FAQ by Student Request/49 - Machine Learning and AI Prerequisite Roadmap pt 1.mp4 141.0 MB
7 - Beginner Troubleshooting/33 - What if I dont meet the math prerequisites.mp4 121.2 MB
10 - Extra Help With Python Coding for Beginners FAQ by Student Request/48 - Proof that using Jupyter Notebook is the same as not using it.mp4 113.3 MB
2 - Numpy New/9 - Generating Data.mp4 90.7 MB
8 - Machine Learning Basics/38 - Regression in Code.mp4 81.0 MB
8 - Machine Learning Basics/35 - What is Classification.mp4 76.3 MB
12 - Appendix FAQ Finale/51 - BONUS.mp4 63.8 MB
1 - Welcome and Logistics/1 - Introduction and Outline.mp4 63.4 MB
2 - Numpy New/4 - Arrays vs Lists.mp4 45.4 MB
3 - Matplotlib New/19 - Where to Learn More Matplotlib.mp4 44.3 MB
2 - Numpy New/12 - Suggestion Box.mp4 41.6 MB
8 - Machine Learning Basics/39 - What is a Feature Vector.mp4 40.4 MB
8 - Machine Learning Basics/42 - Comparing Different Machine Learning Models.mp4 40.4 MB
2 - Numpy New/7 - Matrices.mp4 36.5 MB
8 - Machine Learning Basics/37 - What is Regression.mp4 36.4 MB
8 - Machine Learning Basics/34 - Machine Learning Section Introduction.mp4 35.7 MB

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

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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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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
5. Scipy/3. Sampling from a Gaussian Distribution (Spherical and Axis-aligned Elliptical).mp4 7.9 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. 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
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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
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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
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7. Appendix FAQ/3. Windows-Focused Environment Setup 2018.mp4 195.3 MB
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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
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