- 【影视】 [GigaCourse.Com] Udemy - Machine Learning with SciKit-Learn with Python
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- 9. Cross Validation/13. Performance Analysis on the Test Set.mp4 125.2 MB
- 6. Pandas/6. Remove Operations.mp4 123.1 MB
- 9. Cross Validation/5. PCA Pipeline.mp4 122.9 MB
- 9. Cross Validation/1. Cross Validation.mp4 117.4 MB
- 5. Matlplotlib/3. Multiple Figures and Subplots.mp4 115.7 MB
- 8. Learning and Predicting/4. Persisting Models.mp4 110.3 MB
- 9. Cross Validation/3. K-Means Clustering Example.mp4 109.0 MB
- 6. Pandas/7. Pandas Arithmetic Operations.mp4 108.2 MB
- 6. Pandas/4. Data Structure in Pandas Continue.mp4 107.1 MB
- 8. Learning and Predicting/5. K-NN Algorithm with Example.mp4 106.3 MB
- 3. NumPy Array/6. Numpy Array Splicing.mp4 103.6 MB
- 3. NumPy Array/4. NumPy Array Operations Continue.mp4 97.5 MB
- 9. Cross Validation/15. Language Identifcation.mp4 97.4 MB
- 9. Cross Validation/9. Text Data Example.mp4 94.2 MB
- 3. NumPy Array/8. Stacking Together Different Arrays.mp4 89.7 MB
- 5. Matlplotlib/2. Understanding Various Functions of Pyplot.mp4 89.6 MB
- 9. Cross Validation/14. Parameter Tuning.mp4 89.3 MB
- 6. Pandas/3. Data Structure in Pandas.mp4 88.0 MB
- 6. Pandas/5. Pandas Column Select.mp4 83.4 MB
- 3. NumPy Array/3. NumPy Array Operations.mp4 82.3 MB
- 猜你喜欢: Python SciKit Udemy Machine GigaCourse Learning Learn Com
- 【影视】 [ FreeCourseWeb.com ] RealPython - Real Python - Splitting Datasets With scikit-learn and train_test_split()
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- ~Get Your Files Here !/459 - TTS - 4-2 - A Larger Example.mp4 37.0 MB
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- ~Get Your Files Here !/splitting-datasets-course-slides.pdf 6.5 MB
- ~Get Your Files Here !/459 - TTS - 5 - Other Validation Methods.mp4 6.1 MB
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- 【影视】 [ FreeCourseWeb.com ] Udemy - Machine Learning with SciKit-Learn with Python
- 收录时间:2021-10-15 文档个数:108 文档大小:3.9 GB 最近下载:2024-11-12 人气:3790 磁力链接
- ~Get Your Files Here !/9. Cross Validation/13. Performance Analysis on the Test Set.mp4 125.2 MB
- ~Get Your Files Here !/6. Pandas/6. Remove Operations.mp4 123.1 MB
- ~Get Your Files Here !/9. Cross Validation/5. PCA Pipeline.mp4 122.9 MB
- ~Get Your Files Here !/9. Cross Validation/1. Cross Validation.mp4 117.4 MB
- ~Get Your Files Here !/5. Matlplotlib/3. Multiple Figures and Subplots.mp4 115.7 MB
- ~Get Your Files Here !/8. Learning and Predicting/4. Persisting Models.mp4 110.3 MB
- ~Get Your Files Here !/9. Cross Validation/3. K-Means Clustering Example.mp4 109.0 MB
- ~Get Your Files Here !/6. Pandas/7. Pandas Arithmetic Operations.mp4 108.2 MB
- ~Get Your Files Here !/6. Pandas/4. Data Structure in Pandas Continue.mp4 107.1 MB
- ~Get Your Files Here !/8. Learning and Predicting/5. K-NN Algorithm with Example.mp4 106.3 MB
- ~Get Your Files Here !/3. NumPy Array/6. Numpy Array Splicing.mp4 103.6 MB
- ~Get Your Files Here !/3. NumPy Array/4. NumPy Array Operations Continue.mp4 97.5 MB
- ~Get Your Files Here !/9. Cross Validation/15. Language Identifcation.mp4 97.4 MB
- ~Get Your Files Here !/9. Cross Validation/9. Text Data Example.mp4 94.2 MB
- ~Get Your Files Here !/3. NumPy Array/8. Stacking Together Different Arrays.mp4 89.7 MB
- ~Get Your Files Here !/5. Matlplotlib/2. Understanding Various Functions of Pyplot.mp4 89.6 MB
- ~Get Your Files Here !/9. Cross Validation/14. Parameter Tuning.mp4 89.3 MB
- ~Get Your Files Here !/6. Pandas/3. Data Structure in Pandas.mp4 88.0 MB
- ~Get Your Files Here !/6. Pandas/5. Pandas Column Select.mp4 83.4 MB
- ~Get Your Files Here !/3. NumPy Array/3. NumPy Array Operations.mp4 82.3 MB
- 猜你喜欢: Python SciKit Udemy Machine FreeCourseWeb Learning Learn com
- 【影视】 udemy-machine-learning-101-with-scikit-learn-and-stats-models
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- 5. Linear Regression - Practical Example/1. Practical Example (Part 1).mp4 101.8 MB
- 6. Logistic Regression/3. What is the Difference Between a Logistic and a Logit Function.mp4 79.5 MB
- 7. Cluster Analysis/17. What Can be Done with Cluster Analysis.mp4 66.6 MB
- 7. Cluster Analysis/2. Examples of Clustering.mp4 66.0 MB
- 6. Logistic Regression/14. Underfitting and Overfitting.srt 62.2 MB
- 5. Linear Regression - Practical Example/8. Practical Example (Part 5).mp4 60.7 MB
- 5. Linear Regression - Practical Example/6. Practical Example (Part 4).mp4 58.7 MB
- 1. Introduction/1. What Does the Course Cover.mp4 54.0 MB
- 3. Linear Regression with StatsModels/38. Dealing with Categorical Data.mp4 53.9 MB
- 3. Linear Regression with StatsModels/3. The Linear Regression Model.mp4 53.5 MB
- 7. Cluster Analysis/16. Practical Example Market Segmentation (Part 2).mp4 53.3 MB
- 3. Linear Regression with StatsModels/23. Adjusted R-Squared.mp4 52.1 MB
- 4. Linear Regression with Sklearn/19. Training and Testing.mp4 51.6 MB
- 7. Cluster Analysis/6. A Hands on Example of K-Means.mp4 51.0 MB
- 5. Linear Regression - Practical Example/2. Practical Example (Part 2).mp4 48.2 MB
- 7. Cluster Analysis/1. Introduction to Cluster Analysis.mp4 46.8 MB
- 3. Linear Regression with StatsModels/15. SST, SSR, and SSE.mp4 44.3 MB
- 3. Linear Regression with StatsModels/10. Simple Linear Regression in Python.mp4 43.8 MB
- 2. Setting Up The Working Environment/2. Why Python and Why Jupyter.mp4 43.1 MB
- 3. Linear Regression with StatsModels/13. What Does the StatsModels Summary Regression Table Tell us.mp4 42.9 MB
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- 【其他】 [ DevCourseWeb.com ] Machine Learning with PyTorch and Scikit-Learn - Develop machine learning and deep learning models with Python
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- 9. Cross Validation/13. Performance Analysis on the Test Set.mp4 125.2 MB
- 6. Pandas/6. Remove Operations.mp4 123.1 MB
- 9. Cross Validation/5. PCA Pipeline.mp4 122.9 MB
- 9. Cross Validation/1. Cross Validation.mp4 117.4 MB
- 5. Matlplotlib/3. Multiple Figures and Subplots.mp4 115.7 MB
- 8. Learning and Predicting/4. Persisting Models.mp4 110.3 MB
- 9. Cross Validation/3. K-Means Clustering Example.mp4 109.0 MB
- 6. Pandas/7. Pandas Arithmetic Operations.mp4 108.2 MB
- 6. Pandas/4. Data Structure in Pandas Continue.mp4 107.1 MB
- 8. Learning and Predicting/5. K-NN Algorithm with Example.mp4 106.3 MB
- 3. NumPy Array/6. Numpy Array Splicing.mp4 103.6 MB
- 3. NumPy Array/4. NumPy Array Operations Continue.mp4 97.5 MB
- 9. Cross Validation/15. Language Identifcation.mp4 97.4 MB
- 9. Cross Validation/9. Text Data Example.mp4 94.2 MB
- 3. NumPy Array/8. Stacking Together Different Arrays.mp4 89.7 MB
- 5. Matlplotlib/2. Understanding Various Functions of Pyplot.mp4 89.6 MB
- 9. Cross Validation/14. Parameter Tuning.mp4 89.3 MB
- 6. Pandas/3. Data Structure in Pandas.mp4 88.0 MB
- 6. Pandas/5. Pandas Column Select.mp4 83.4 MB
- 3. NumPy Array/3. NumPy Array Operations.mp4 82.3 MB
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- 【影视】 Building Image Processing Applications Using scikit-image (Janani Ravi, 2018)
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- 4. Segmentation and Transformation/10. Comparing Images Using MSE and SSIM.mp4 23.2 MB
- exercise.7z 21.8 MB
- 3. Object and Feature Detection/7. Applying Denoising Filters.mp4 17.2 MB
- 3. Object and Feature Detection/9. Filling Holes and Finding Peaks Using Erosion and Dilation.mp4 17.0 MB
- 2. Working with Image Data/05. Working with Images as NumPy Arrays.mp4 14.3 MB
- 4. Segmentation and Transformation/03. Applying Global and Local Thresholding Algorithms.mp4 12.2 MB
- 4. Segmentation and Transformation/05. Segmentation and Merging Segments Using Rags.mp4 11.9 MB
- 2. Working with Image Data/14. Canny Edge Detection.mp4 11.1 MB
- 2. Working with Image Data/10. Contours.mp4 10.6 MB
- 4. Segmentation and Transformation/08. Applying Image Transformations.mp4 9.9 MB
- 3. Object and Feature Detection/5. Corner Detection.mp4 9.7 MB
- 3. Object and Feature Detection/4. Visualizing Hog Feature Descriptors.mp4 9.6 MB
- 3. Object and Feature Detection/3. Visualizing Daisy Descriptors on Images.mp4 9.5 MB
- 2. Working with Image Data/09. Block Views and Pooling Operations.mp4 9.1 MB
- 2. Working with Image Data/07. Masking Color Images.mp4 8.4 MB
- 4. Segmentation and Transformation/07. Segmentation Using Classic and Compact Watershed.mp4 7.9 MB
- 2. Working with Image Data/06. Masking Images Using Array Manipulation.mp4 7.8 MB
- 2. Working with Image Data/04. Introducing scikit-image.mp4 6.6 MB
- 2. Working with Image Data/11. Convex Hull.mp4 5.3 MB
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