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种子名称： [DesireCourse.Net] Udemy - Practical Machine Learning by Example in Python
文件类型： 视频
文件数目： 101个文件
文件大小： 2.71 GB
收录时间： 2021-10-6 23:48
已经下载： 3次
资源热度： 289
最近下载： 2024-11-10 14:30

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[DesireCourse.Net] Udemy - Practical Machine Learning by Example in Python.torrent

1. Course Structure and Development Environment/1. Course Structure and Development Environment.mp431.37MB

1. Course Structure and Development Environment/2. Course Quick Tips.mp432.08MB

1. Course Structure and Development Environment/3. Introduction to Jupyter Notebook.mp416.92MB

1. Course Structure and Development Environment/4. Jupyter notebook Text Cells.mp427.07MB

1. Course Structure and Development Environment/5. Jupyter notebook Code Cells.mp415.03MB

1. Course Structure and Development Environment/6. Jupyter notebook Math Markup and Magic Commands.mp423.35MB

1. Course Structure and Development Environment/8. Sharing Colab Notebooks.mp435.7MB

1. Course Structure and Development Environment/9. Artificial Intelligence, Machine Learning, and Deep Learning.mp425.15MB

10. Example Fraud detection/1. The problem.mp422.34MB

10. Example Fraud detection/11. Common questions.mp428.84MB

10. Example Fraud detection/2. Data analysis.mp441.75MB

10. Example Fraud detection/4. Unsupervised learning.mp428.85MB

10. Example Fraud detection/5. Data preparation.mp416.86MB

10. Example Fraud detection/6. Model definition.mp421.42MB

10. Example Fraud detection/7. Model training.mp425.11MB

10. Example Fraud detection/9. Making predictions.mp449.37MB

11. Next steps/1. Next steps.mp411.59MB

11. Next steps/2. Thank you.mp43.07MB

2. Python Quick Start/1. About this section.mp47.44MB

2. Python Quick Start/10. Dictionaries.mp432.06MB

2. Python Quick Start/11. Defining functions.mp434.67MB

2. Python Quick Start/12. Classes.mp462.46MB

2. Python Quick Start/13. File IO and Modules.mp433.75MB

2. Python Quick Start/15. Prompting for passwords.mp47.09MB

2. Python Quick Start/2. Basic Syntax.mp435.16MB

2. Python Quick Start/3. String formatting.mp452.36MB

2. Python Quick Start/4. Literal string interpolation.mp415.79MB

2. Python Quick Start/6. Type conversion.mp419.6MB

2. Python Quick Start/7. Flow control.mp423.5MB

2. Python Quick Start/8. Lists.mp422.36MB

3. Example Logistic Regression/1. The problem.mp427.97MB

3. Example Logistic Regression/10. Backpropagation.mp423.91MB

3. Example Logistic Regression/11. Model training.mp429.92MB

3. Example Logistic Regression/12. Making predictions.mp440.33MB

3. Example Logistic Regression/15. Test vs. train accuracy.mp418.97MB

3. Example Logistic Regression/16. Speeding up training.mp418.1MB

3. Example Logistic Regression/17. Improving the model.mp427.09MB

3. Example Logistic Regression/2. Machine Learning Development Process.mp414.03MB

3. Example Logistic Regression/3. Data analysis.mp458.98MB

3. Example Logistic Regression/5. The model.mp422.19MB

3. Example Logistic Regression/6. The forward function.mp437.85MB

3. Example Logistic Regression/7. Loss and cost functions.mp419.82MB

3. Example Logistic Regression/8. Gradient descent.mp446.27MB

4. Foundations NumPy/1. What is NumPy and why it is needed.mp48.12MB

4. Foundations NumPy/10. Visualizing data.mp433.72MB

4. Foundations NumPy/11. Images.mp431.8MB

4. Foundations NumPy/13. Reshaping data.mp411.15MB

4. Foundations NumPy/2. Creating data with NumPy.mp425MB

4. Foundations NumPy/3. Basic operations.mp414.7MB

4. Foundations NumPy/5. Introduction to Linear Regression.mp452.3MB

4. Foundations NumPy/6. Linear Regression Example.mp464.63MB

4. Foundations NumPy/8. More Complex Models.mp413.51MB

4. Foundations NumPy/9. Statistics and linear algebra.mp416.96MB

5. Foundations Tensorflow/1. About this section.mp418.09MB

5. Foundations Tensorflow/10. Prediction example.mp46.78MB

5. Foundations Tensorflow/11. Saving and restoring models.mp415.58MB

5. Foundations Tensorflow/12. The Three Body Problem.mp423.47MB

5. Foundations Tensorflow/2. Model example.mp428.95MB

5. Foundations Tensorflow/3. Model layers.mp413.2MB

5. Foundations Tensorflow/4. Activation functions.mp419.33MB

5. Foundations Tensorflow/5. Training example.mp423.54MB

5. Foundations Tensorflow/7. Loss functions.mp419.2MB

5. Foundations Tensorflow/8. Optimizers.mp416.4MB

6. Example Image recognition/1. The problem.mp419.42MB

6. Example Image recognition/10. Making predictions.mp412.29MB

6. Example Image recognition/11. Error analysis.mp415.42MB

6. Example Image recognition/13. Hyperparameter tuning.mp422.44MB

6. Example Image recognition/14. Hyperparameter tuning example.mp452.48MB

6. Example Image recognition/16. Common questions.mp427.85MB

6. Example Image recognition/2. Data analysis.mp438.32MB

6. Example Image recognition/4. Model selection.mp422.78MB

6. Example Image recognition/5. Data preparation.mp427MB

6. Example Image recognition/6. CNN Model Layers.mp422.97MB

6. Example Image recognition/7. Model definition.mp431.7MB

6. Example Image recognition/8. Model training.mp450.24MB

7. Foundations Pandas/1. What is Pandas and why is it useful.mp48.92MB

7. Foundations Pandas/2. Loading and inspecting data example.mp458.99MB

7. Foundations Pandas/3. Indexing and selecting data example.mp434.96MB

7. Foundations Pandas/5. Sorting and transforming data example.mp439.83MB

7. Foundations Pandas/6. Aggregations example.mp433.94MB

7. Foundations Pandas/7. Visualizing data.mp435.32MB

8. Example Recommendations/1. The problem.mp417.06MB

8. Example Recommendations/11. Predictions.mp45.7MB

8. Example Recommendations/12. Making predictions.mp429.53MB

8. Example Recommendations/13. Error analysis.mp418.61MB

8. Example Recommendations/15. Common questions.mp419.57MB

8. Example Recommendations/2. Data analysis.mp429.05MB

8. Example Recommendations/4. Model selection.mp426.96MB

8. Example Recommendations/5. Data preparation.mp436.17MB

8. Example Recommendations/7. Embedding layers.mp417.17MB

8. Example Recommendations/8. Model definition.mp442.25MB

8. Example Recommendations/9. Model training.mp429.34MB

9. Example Sentiment Analysis/1. The Problem.mp413.13MB

9. Example Sentiment Analysis/10. Transfer Learning with BERT.mp423.75MB

9. Example Sentiment Analysis/11. Transfer Learning Example.mp457.83MB

9. Example Sentiment Analysis/12. Fine Tuning and Prediction.mp439.54MB

9. Example Sentiment Analysis/2. Data Analysis.mp430.54MB

9. Example Sentiment Analysis/4. Supervised Learning.mp427.63MB

9. Example Sentiment Analysis/5. Data Preparation.mp444.37MB

9. Example Sentiment Analysis/7. Model Definition.mp429.01MB

9. Example Sentiment Analysis/8. Model Training.mp434.77MB