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[UdemyCourseDownloader] The Complete Self-Driving Car Course - Applied Deep Learning

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种子名称: [UdemyCourseDownloader] The Complete Self-Driving Car Course - Applied Deep Learning
文件类型: 视频
文件数目: 138个文件
文件大小: 9.19 GB
收录时间: 2019-2-7 21:31
已经下载: 3
资源热度: 259
最近下载: 2024-5-13 08:14

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[UdemyCourseDownloader] The Complete Self-Driving Car Course - Applied Deep Learning.torrent
  • 14. Behavioural Cloning/11. Generator - Augmentation Techniques.mp4380.89MB
  • 1. Introduction/1. Why This Course.mp425.87MB
  • 2. Installation/1. Overview.mp45.9MB
  • 2. Installation/2. Anaconda Distribution - Mac.mp425.24MB
  • 2. Installation/3. Anaconda Distribution - Windows.mp425.31MB
  • 2. Installation/4. Text Editor.mp429.1MB
  • 2. Installation/5. Outro.mp45.53MB
  • 3. Python Crash Course (Optional)/1. Python Crash Course Part 1 - Data Types.mp415.23MB
  • 3. Python Crash Course (Optional)/2. Jupyter Notebooks.mp49.98MB
  • 3. Python Crash Course (Optional)/3. Arithmetic Operations.mp425.44MB
  • 3. Python Crash Course (Optional)/4. Variables.mp427.68MB
  • 3. Python Crash Course (Optional)/5. Numeric Data Types.mp423.51MB
  • 3. Python Crash Course (Optional)/6. String Data Types.mp441.96MB
  • 3. Python Crash Course (Optional)/7. Booleans.mp424.24MB
  • 3. Python Crash Course (Optional)/8. Methods.mp420.7MB
  • 3. Python Crash Course (Optional)/9. Lists.mp435.82MB
  • 3. Python Crash Course (Optional)/10. Slicing.mp455.56MB
  • 3. Python Crash Course (Optional)/11. Membership Operators.mp413.79MB
  • 3. Python Crash Course (Optional)/12. Mutability.mp432.97MB
  • 3. Python Crash Course (Optional)/13. Mutability II.mp431.64MB
  • 3. Python Crash Course (Optional)/14. Common Functions & Methods.mp446.79MB
  • 3. Python Crash Course (Optional)/15. Tuples.mp423.06MB
  • 3. Python Crash Course (Optional)/16. Sets.mp419.64MB
  • 3. Python Crash Course (Optional)/17. Dictionaries.mp435.35MB
  • 3. Python Crash Course (Optional)/18. Compound Data Structures.mp420.19MB
  • 3. Python Crash Course (Optional)/19. Part 1 - Outro.mp43.62MB
  • 3. Python Crash Course (Optional)/20. Part 2 - Control Flow.mp411.48MB
  • 3. Python Crash Course (Optional)/21. If, else.mp427.17MB
  • 3. Python Crash Course (Optional)/22. elif.mp449.04MB
  • 3. Python Crash Course (Optional)/23. Complex Comparisons.mp429.53MB
  • 3. Python Crash Course (Optional)/24. For Loops.mp438.5MB
  • 3. Python Crash Course (Optional)/25. For Loops II.mp415.07MB
  • 3. Python Crash Course (Optional)/26. While Loops.mp420.2MB
  • 3. Python Crash Course (Optional)/27. Break.mp419.72MB
  • 3. Python Crash Course (Optional)/28. Part 2 - Outro.mp44.48MB
  • 3. Python Crash Course (Optional)/29. Part 3 - Functions.mp411.43MB
  • 3. Python Crash Course (Optional)/30. Functions.mp431.62MB
  • 3. Python Crash Course (Optional)/31. Scope.mp413.17MB
  • 3. Python Crash Course (Optional)/32. Doc Strings.mp419.59MB
  • 3. Python Crash Course (Optional)/33. Lambda & Higher Order Functions.mp428.4MB
  • 3. Python Crash Course (Optional)/34. 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.mp496.82MB
  • 4. NumPy Crash Course (Optional)/4. One Dimensional Slicing.mp425.03MB
  • 4. NumPy Crash Course (Optional)/5. Reshaping.mp423.41MB
  • 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.mp482.31MB
  • 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 Image.mp440.23MB
  • 5. Computer Vision Finding Lane Lines/4. Grayscale Conversion.mp447.23MB
  • 5. Computer Vision Finding Lane Lines/5. Smoothening Image.mp430.57MB
  • 5. Computer Vision Finding Lane Lines/6. Simple Edge Detection.mp442.64MB
  • 5. Computer Vision Finding Lane Lines/7. Region of Interest.mp449.33MB
  • 5. Computer Vision Finding Lane Lines/8. Binary Numbers & Bitwise_and.mp491.8MB
  • 5. Computer Vision Finding Lane Lines/9. Line Detection - 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.mp431.93MB
  • 5. Computer Vision Finding Lane Lines/15. Part 5 - Conclusion.mp410.23MB
  • 6. The Perceptron/1. Overview.mp427.76MB
  • 6. The Perceptron/2. Machine Learning.mp437.03MB
  • 6. The Perceptron/3. Supervised Learning - Friendly Example.mp446.59MB
  • 6. The Perceptron/4. Classification.mp482.08MB
  • 6. The Perceptron/5. Linear Model.mp486.36MB
  • 6. The Perceptron/6. Perceptrons.mp450.68MB
  • 6. The Perceptron/7. Weights.mp425.29MB
  • 6. The Perceptron/8. Project - Initial Stages.mp478.25MB
  • 6. The Perceptron/10. Error Function.mp441.63MB
  • 6. The Perceptron/11. Sigmoid.mp461.73MB
  • 6. The Perceptron/12. Sigmoid Implementation (Code).mp490.73MB
  • 6. The Perceptron/14. Cross Entropy.mp462.73MB
  • 6. The Perceptron/15. Cross Entropy (Code).mp461.25MB
  • 6. The Perceptron/17. Gradient Descent.mp445.18MB
  • 6. The Perceptron/18. Gradient Descent (Code).mp475.74MB
  • 6. The Perceptron/19. Recap.mp417.74MB
  • 6. The Perceptron/21. Part 6 - Conclusion.mp49.69MB
  • 7. Keras/1. Overview.mp46.81MB
  • 7. Keras/2. Intro to Keras.mp419.98MB
  • 7. Keras/4. Keras Models.mp4175.26MB
  • 7. Keras/5. Keras - Predictions.mp4144.46MB
  • 7. Keras/7. Part 7 - Outro.mp44.83MB
  • 8. Deep Neural Networks/1. Overview.mp415.65MB
  • 8. Deep Neural Networks/2. Non-Linear Boundaries.mp471.12MB
  • 8. Deep Neural Networks/3. Architecture.mp4126.03MB
  • 8. Deep Neural Networks/4. Feedforward Process.mp488.9MB
  • 8. Deep Neural Networks/5. Error Function.mp454.07MB
  • 8. Deep Neural Networks/6. Backpropagation.mp465.4MB
  • 8. Deep Neural Networks/7. Code Implementation.mp4204.25MB
  • 8. Deep Neural Networks/9. Section 8 - Conclusion.mp46.02MB
  • 9. Multiclass Classification/1. Overview.mp410.4MB
  • 9. Multiclass Classification/2. Softmax.mp4141.67MB
  • 9. Multiclass Classification/3. Cross Entropy.mp481.95MB
  • 9. Multiclass Classification/4. Implementation.mp4245.3MB
  • 9. Multiclass Classification/6. Section 9 - Outro.mp45.4MB
  • 10. MNIST Image Recognition/1. Overview.mp410.83MB
  • 10. MNIST Image Recognition/2. MNIST Dataset.mp470.96MB
  • 10. MNIST Image Recognition/3. Train & Test.mp4132.04MB
  • 10. MNIST Image Recognition/4. Hyperparameters.mp481.23MB
  • 10. MNIST Image Recognition/5. Implementation Part 1.mp4194.02MB
  • 10. MNIST Image Recognition/6. Implementation Part 2.mp4155.9MB
  • 10. MNIST Image Recognition/8. Implementation Part 3.mp475.33MB
  • 10. MNIST Image Recognition/10. Section 10 - Outro.mp45.96MB
  • 11. Convolutional Neural Networks/1. Overview.mp49.63MB
  • 11. Convolutional Neural Networks/2. Convolutions & MNIST.mp489.98MB
  • 11. Convolutional Neural Networks/3. Convolutional Layer.mp4229.8MB
  • 11. Convolutional Neural Networks/4. Convolutions II.mp479.79MB
  • 11. Convolutional Neural Networks/5. Pooling.mp4161.92MB
  • 11. Convolutional Neural Networks/6. Fully Connected Layer.mp477.89MB
  • 11. Convolutional Neural Networks/8. Code Implementation I.mp4254.53MB
  • 11. Convolutional Neural Networks/9. Code Implementation II.mp4213.41MB
  • 11. Convolutional Neural Networks/11. Section 11 - Conclusion.mp44.77MB
  • 12. Classifying Road Symbols/1. Overview.mp414.49MB
  • 12. Classifying Road Symbols/3. Preprocessing Images.mp4330.4MB
  • 12. Classifying Road Symbols/4. leNet Implementation.mp4129.39MB
  • 12. Classifying Road Symbols/5. Fine-tuning Model.mp4117.04MB
  • 12. Classifying Road Symbols/7. Testing.mp463.15MB
  • 12. Classifying Road Symbols/8. Fit Generator.mp4159.84MB
  • 12. Classifying Road Symbols/10. Section 12 - Outro.mp49.93MB
  • 13. Polynomial Regression/1. Overview.mp47.55MB
  • 13. Polynomial Regression/2. Implementation.mp4128.86MB
  • 13. Polynomial Regression/4. Section 13 - Conclusion.mp45.19MB
  • 14. Behavioural Cloning/1. Overview.mp450.21MB
  • 14. Behavioural Cloning/2. Collecting Data.mp4282.41MB
  • 14. Behavioural Cloning/3. Downloading Data.mp4130.62MB
  • 14. Behavioural Cloning/4. Balancing Data.mp474.71MB
  • 14. Behavioural Cloning/5. Training & Validation Split.mp465.74MB
  • 14. Behavioural Cloning/6. Preprocessing Images.mp4161.75MB
  • 14. Behavioural Cloning/7. Defining Nvidia Model.mp4198.55MB
  • 14. Behavioural Cloning/9. Flask & Socket.io.mp499.77MB
  • 14. Behavioural Cloning/10. Self Driving Car - Test 1.mp4165.97MB
  • 14. Behavioural Cloning/12. Batch Generator.mp495.11MB
  • 14. Behavioural Cloning/13. Fit Generator.mp4248.41MB
  • 14. Behavioural Cloning/15. Outro.mp419.58MB