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种子名称： The Complete Self-Driving Car Course - Applied Deep Learning
文件类型： 视频
文件数目： 139个文件
文件大小： 8.23 GB
收录时间： 2020-11-16 11:45
已经下载： 3次
资源热度： 306
最近下载： 2024-12-24 16:28

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The Complete Self-Driving Car Course - Applied Deep Learning.torrent

12. Traffic Sign Classification/3. Preprocessing Images.mp4330.4MB

2. Installation/1. Overview.mp410.49MB

2. Installation/2. Anaconda Distribution.mp426.28MB

2. Installation/3. Jupyter Notebooks.mp441.92MB

2. Installation/4. Text Editor.mp429.09MB

2. Installation/5. Outro.mp45.52MB

3. Python Crash Course (Optional)/1. Python Crash Course Part 1 - Data Types.mp415.22MB

3. Python Crash Course (Optional)/2. Arithmetic Operations.mp425.43MB

3. Python Crash Course (Optional)/3. Variables.mp427.67MB

3. Python Crash Course (Optional)/4. Numeric Data Types.mp423.5MB

3. Python Crash Course (Optional)/5. String Data Types.mp441.95MB

3. Python Crash Course (Optional)/6. Booleans.mp424.24MB

3. Python Crash Course (Optional)/7. Methods.mp420.69MB

3. Python Crash Course (Optional)/8. Lists.mp435.82MB

3. Python Crash Course (Optional)/9. Slicing.mp455.55MB

3. Python Crash Course (Optional)/10. Membership Operators.mp413.78MB

3. Python Crash Course (Optional)/11. Mutability.mp432.97MB

3. Python Crash Course (Optional)/12. Mutability II.mp431.64MB

3. Python Crash Course (Optional)/13. Common Functions & Methods.mp446.79MB

3. Python Crash Course (Optional)/14. Tuples.mp423.05MB

3. Python Crash Course (Optional)/15. Sets.mp419.64MB

3. Python Crash Course (Optional)/16. Dictionaries.mp435.34MB

3. Python Crash Course (Optional)/17. Compound Data Structures.mp420.19MB

3. Python Crash Course (Optional)/18. Part 1 - Outro.mp43.62MB

3. Python Crash Course (Optional)/19. Part 2 - Control Flow.mp411.47MB

3. Python Crash Course (Optional)/20. If, else.mp427.16MB

3. Python Crash Course (Optional)/21. elif.mp449.03MB

3. Python Crash Course (Optional)/22. Complex Comparisons.mp429.52MB

3. Python Crash Course (Optional)/23. For Loops.mp438.49MB

3. Python Crash Course (Optional)/24. For Loops II.mp415.06MB

3. Python Crash Course (Optional)/25. While Loops.mp420.19MB

3. Python Crash Course (Optional)/26. Break.mp419.71MB

3. Python Crash Course (Optional)/27. Part 2 - Outro.mp44.48MB

3. Python Crash Course (Optional)/28. Part 3 - Functions.mp411.43MB

3. Python Crash Course (Optional)/29. Functions.mp431.62MB

3. Python Crash Course (Optional)/30. Scope.mp413.16MB

3. Python Crash Course (Optional)/31. Doc Strings.mp419.59MB

3. Python Crash Course (Optional)/32. Lambda & Higher Order Functions.mp428.39MB

3. Python Crash Course (Optional)/33. Part 3 - Outro.mp48.84MB

4. NumPy Crash Course (Optional)/1. Overview.mp410.59MB

4. NumPy Crash Course (Optional)/2. Vector Addition - Arrays vs Lists.mp486.82MB

4. NumPy Crash Course (Optional)/3. Multidimensional Arrays.mp496.81MB

4. NumPy Crash Course (Optional)/4. One Dimensional Slicing.mp427.77MB

4. NumPy Crash Course (Optional)/5. Reshaping.mp423.4MB

4. NumPy Crash Course (Optional)/6. Multidimensional Slicing.mp449.16MB

4. NumPy Crash Course (Optional)/7. Manipulating Array Shapes.mp447.76MB

4. NumPy Crash Course (Optional)/8. Matrix Multiplication.mp434.28MB

4. NumPy Crash Course (Optional)/9. Stacking.mp482.3MB

4. NumPy Crash Course (Optional)/10. Part 4 - Outro.mp42.48MB

5. Computer Vision Finding Lane-Lines/1. Overview.mp49MB

5. Computer Vision Finding Lane-Lines/3. Loading Images.mp430.72MB

5. Computer Vision Finding Lane-Lines/4. Grayscale.mp447.23MB

5. Computer Vision Finding Lane-Lines/5. Gaussian Blur.mp430.56MB

5. Computer Vision Finding Lane-Lines/6. Canny Edge Detection.mp442.63MB

5. Computer Vision Finding Lane-Lines/7. Region of Interest.mp449.32MB

5. Computer Vision Finding Lane-Lines/8. Binary Numbers & Bitwise_and.mp491.79MB

5. Computer Vision Finding Lane-Lines/9. Hough Transform.mp4132.64MB

5. Computer Vision Finding Lane-Lines/10. Hough Transform II.mp4114.7MB

5. Computer Vision Finding Lane-Lines/11. Optimizing.mp4164.52MB

5. Computer Vision Finding Lane-Lines/13. Finding Lanes on Video.mp482.8MB

5. Computer Vision Finding Lane-Lines/13.1 test2.mp4.mp431.92MB

5. Computer Vision Finding Lane-Lines/15. Part 5 - Conclusion.mp410.23MB

6. Intro to Neural Networks/1. Overview.mp427.76MB

6. Intro to Neural Networks/2. Machine Learning.mp437.03MB

6. Intro to Neural Networks/3. Linear Regression.mp446.58MB

6. Intro to Neural Networks/4. Classification.mp482.07MB

6. Intro to Neural Networks/5. Linear Model.mp486.36MB

6. Intro to Neural Networks/6. Perceptrons.mp450.67MB

6. Intro to Neural Networks/7. Weights.mp425.29MB

6. Intro to Neural Networks/8. Project - Initial Stages.mp478.25MB

6. Intro to Neural Networks/10. Error Function.mp441.63MB

6. Intro to Neural Networks/11. Sigmoid.mp461.73MB

6. Intro to Neural Networks/12. Sigmoid Implementation (Code).mp490.73MB

6. Intro to Neural Networks/14. Cross Entropy.mp462.72MB

6. Intro to Neural Networks/15. Cross Entropy (Code).mp461.24MB

6. Intro to Neural Networks/17. Gradient Descent.mp445.18MB

6. Intro to Neural Networks/18. Gradient Descent (Code).mp475.74MB

6. Intro to Neural Networks/19. Recap.mp417.74MB

6. Intro to Neural Networks/21. Part 6 - Conclusion.mp49.69MB

7. Keras/1. Overview.mp46.8MB

7. Keras/2. Intro to Keras.mp421.45MB

7. Keras/4. Keras Models.mp4175.26MB

7. Keras/5. Keras - Predictions.mp4144.45MB

7. Keras/7. Part 7 - Outro.mp44.82MB

8. Deep Neural Networks/1. Overview.mp415.64MB

8. Deep Neural Networks/2. Non-Linear Boundaries.mp471.11MB

8. Deep Neural Networks/3. Architecture.mp4126.02MB

8. Deep Neural Networks/4. Feedforward Process.mp488.89MB

8. Deep Neural Networks/5. Error Function.mp454.06MB

8. Deep Neural Networks/6. Backpropagation.mp465.39MB

8. Deep Neural Networks/7. Code Implementation.mp4204.24MB

8. Deep Neural Networks/9. Section 8 - Conclusion.mp46.01MB

9. Multiclass Classification/1. Overview.mp410.39MB

9. Multiclass Classification/2. Softmax.mp4141.66MB

9. Multiclass Classification/3. Cross Entropy.mp481.94MB

9. Multiclass Classification/4. Implementation.mp4245.29MB

9. Multiclass Classification/6. Section 9 - Outro.mp45.39MB

10. MNIST Image Recognition/1. Overview.mp410.82MB

10. MNIST Image Recognition/2. MNIST Dataset.mp470.95MB

10. MNIST Image Recognition/3. Train & Test.mp4132.03MB

10. MNIST Image Recognition/4. Hyperparameters.mp481.22MB

10. MNIST Image Recognition/5. Implementation Part 1.mp4194.01MB

10. MNIST Image Recognition/6. Implementation Part 2.mp4155.89MB

10. MNIST Image Recognition/8. Implementation Part 3.mp475.32MB

10. MNIST Image Recognition/10. Section 10 - Outro.mp45.95MB

11. Convolutional Neural Networks/1. Overview.mp49.62MB

11. Convolutional Neural Networks/2. Convolutions & MNIST.mp489.98MB

11. Convolutional Neural Networks/3. Convolutional Layer.mp4229.79MB

11. Convolutional Neural Networks/4. Convolutions II.mp479.78MB

11. Convolutional Neural Networks/5. Pooling.mp4161.91MB

11. Convolutional Neural Networks/6. Fully Connected Layer.mp477.89MB

11. Convolutional Neural Networks/8. Code Implementation I.mp4254.52MB

11. Convolutional Neural Networks/9. Code Implementation II.mp4213.4MB

11. Convolutional Neural Networks/11. Section 11 - Conclusion.mp44.76MB

12. Traffic Sign Classification/1. Overview.mp414.48MB

1. Introduction/1. Introduction.mp440.45MB

12. Traffic Sign Classification/4. leNet Implementation.mp4129.38MB

12. Traffic Sign Classification/5. Fine-tuning Model.mp4117.04MB

12. Traffic Sign Classification/7. Testing.mp463.14MB

12. Traffic Sign Classification/8. Fit Generator.mp4159.83MB

12. Traffic Sign Classification/10. Section 12 - Outro.mp49.92MB

13. Polynomial Regression/1. Overview.mp47.54MB

13. Polynomial Regression/2. Implementation.mp4128.85MB

13. Polynomial Regression/4. Section 13 - Conclusion.mp45.18MB

14. Behavioural Cloning/1. Overview.mp450.21MB

14. Behavioural Cloning/2. Collecting Data.mp4282.4MB

14. Behavioural Cloning/3. Downloading Data.mp4130.61MB

14. Behavioural Cloning/4. Balancing Data.mp474.71MB

14. Behavioural Cloning/5. Training & Validation Split.mp465.73MB

14. Behavioural Cloning/6. Preprocessing Images.mp4161.74MB

14. Behavioural Cloning/7. Defining Nvidia Model.mp4198.54MB

14. Behavioural Cloning/9. Flask & Socket.io.mp4351B

14. Behavioural Cloning/10. Self Driving Car - Test 1.mp4351B

14. Behavioural Cloning/11. Generator - Augmentation Techniques.mp4351B

14. Behavioural Cloning/12. Batch Generator.mp4351B

14. Behavioural Cloning/13. Fit Generator.mp4351B

14. Behavioural Cloning/15. Outro.mp4351B

15. Final Codes & Outputs/12. Simulation Output Results - Training Track.mp4351B

15. Final Codes & Outputs/13. Simulation Output Results - Test Track.mp4351B