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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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- 6. Appendix FAQ/3. Windows-Focused Environment Setup 2018.mp4 195.3 MB
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- 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
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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
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- 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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- 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
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- 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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- Chapter 6 Machine Learning Basics/003. Classification in Code.mp4 84.9 MB
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- 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
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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/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
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- 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
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- 6. Appendix/3. Windows-Focused Environment Setup 2018.vtt 195.3 MB
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- 6. Appendix/6. 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 46.0 MB
- 6. Appendix/8. What order should I take your courses in (part 2).mp4 39.5 MB
- 6. Appendix/2. Bonus Section on Machine Learning Basics.mp4 36.7 MB
- 3. Pandas/7. .values vs .as_matrix().mp4 34.9 MB
- 6. Appendix/7. What order should I take your courses in (part 1).mp4 30.8 MB
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- 4. Matplotlib/4. Plotting Images.mp4 12.7 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
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- ~Get Your Files Here !/3 - Configure Azure resources with tools/7 - Interactive lab Azure PowerShell.mp4 72.6 MB
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- ~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
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- ~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
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- 4. Matplotlib/4. Plotting Images.mp4 12.8 MB
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- 1. Introduction and Outline/1. What’s this course about How can you succeed What should you know first.mp4 10.6 MB
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- 收录时间:2022-10-08 文档个数:43 文档大小:507.1 MB 最近下载:2024-10-02 人气:1267 磁力链接
- ~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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- 【压缩文件】 [ FreeCourseWeb.com ] Udemy - Machine Learning Prerequisites for 2021.zip
- 收录时间:2021-01-30 文档个数:1 文档大小:485.3 MB 最近下载:2024-09-13 人气:1394 磁力链接
- [ FreeCourseWeb.com ] Udemy - Machine Learning Prerequisites for 2021.zip 485.3 MB
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- 【影视】 [UdemyCourseDownloader] Deep Learning Prerequisites Logistic Regression in Python
- 收录时间:2020-02-10 文档个数:41 文档大小:445.1 MB 最近下载:2024-09-29 人气:285 磁力链接
- 07 Appendix/036 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp4 46.0 MB
- 04 Practical concerns/026 The donut problem.mp4 25.9 MB
- 07 Appendix/037 How to Code by Yourself part 1.mp4 25.7 MB
- 06 Project Facial Expression Recognition/034 Facial Expression Recognition in Code.mp4 25.2 MB
- 06 Project Facial Expression Recognition/031 Facial Expression Recognition Problem Description.mp4 22.5 MB
- 03 Solving for the optimal weights/019 E-Commerce Course Project Training the Logistic Model.mp4 17.9 MB
- 07 Appendix/038 How to Code by Yourself part 2.mp4 15.5 MB
- 01 Start Here/004 Introduction to the E-Commerce Course Project.mp4 15.5 MB
- 04 Practical concerns/021 L2 Regularization - Theory.mp4 15.4 MB
- 04 Practical concerns/027 The XOR problem.mp4 14.9 MB
- 06 Project Facial Expression Recognition/033 Utilities walkthrough.mp4 14.1 MB
- 03 Solving for the optimal weights/016 Maximizing the likelihood.mp4 13.3 MB
- 04 Practical concerns/024 L1 Regularization - Code.mp4 12.6 MB
- 05 Checkpoint and applications How to make sure you know your stuff/028 BONUS Sentiment Analysis.mp4 12.0 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
- 06 Project Facial Expression Recognition/032 The class imbalance problem.mp4 10.6 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/017 Updating the weights using gradient descent - Theory.mp4 9.8 MB
- 03 Solving for the optimal weights/014 The cross-entropy error function - Code.mp4 9.5 MB
- 01 Start Here/002 How to Succeed in this Course.mp4 9.2 MB
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- 【压缩文件】 [DesireCourse.Com] Udemy - Deep Learning Prerequisites Linear Regression in Python
- 收录时间:2020-04-23 文档个数:3 文档大小:352.9 MB 最近下载:2024-10-07 人气:5162 磁力链接
- [DesireCourse.Com] Udemy - Deep Learning Prerequisites Linear Regression in Python.zip 352.9 MB
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