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[FreeCourseSite.com] Udemy - Autonomous Cars Deep Learning and Computer Vision in Python

FreeCourseSiteUdemyAutonomousCarsDeepLearningComputerVisionPython

种子大小：7.36 GB

收录时间：2023-07-21

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文件列表：188File

  1. 9. Artificial Neural Networks/10. Example 1 - Build Multi-layer perceptron for binary classification.mp4384.19 MB
  2. 8. Machine Learning Part 2/6. [Activity] Detecting Cars Using SVM - Part #2.mp4204.08 MB
  3. 11. Deep Learning and Tensorflow Part 2/8. [Activity] Build a CNN to Classify Traffic Siigns - part 2.mp4175.33 MB
  4. 6. Computer Vision Basics Part 3/11. Histogram of Oriented Gradients (HOG).mp4169.49 MB
  5. 4. Computer Vision Basics Part 1/9. [Activity] Convert RGB to HSV color spaces and mergesplit channels.mp4166.92 MB
  6. 9. Artificial Neural Networks/4. ANN Training and dataset split.mp4151.3 MB
  7. 11. Deep Learning and Tensorflow Part 2/7. [Activity] Build a CNN to Classify Traffic Signs.mp4150.58 MB
  8. 3. Python Crash Course [Optional]/7. Introduction to Seaborn.mp4146.72 MB
  9. 2. Introduction to Self-Driving Cars/1. A Brief History of Autonomous Vehicles.mp4145.92 MB
  10. 5. Computer Vision Basics Part 2/9. Hough transform theory.mp4141.5 MB
  11. 4. Computer Vision Basics Part 1/2. Humans vs. Computers Vision system.mp4135.32 MB
  12. 10. Deep Learning and Tensorflow Part 1/3. [Activity] Building a Logistic Classifier with Deep Learning and Keras.mp4134.56 MB
  13. 9. Artificial Neural Networks/1. Introduction What are Artificial Neural Networks and how do they learn.mp4127.77 MB
  14. 8. Machine Learning Part 2/5. Project Solution Detecting Cars Using SVM - Part #1.mp4119.72 MB
  15. 9. Artificial Neural Networks/2. Single Neuron Perceptron Model.mp4119.67 MB
  16. 4. Computer Vision Basics Part 1/1. What is computer vision and why is it important.mp4118.76 MB
  17. 5. Computer Vision Basics Part 2/11. Project Solution Hough transform to detect lane lines in an image.mp4117.05 MB
  18. 8. Machine Learning Part 2/7. [Activity] Project Solution Detecting Cars Using SVM - Part #3.mp4116.83 MB
  19. 4. Computer Vision Basics Part 1/8. Color Spaces.mp4113.66 MB
  20. 9. Artificial Neural Networks/6. Code to build a perceptron for binary classification.mp4111.6 MB
  21. 9. Artificial Neural Networks/8. Code to Train a perceptron for binary classification.mp4110.23 MB
  22. 7. Machine Learning Part 1/8. [Activity] Decision Trees In Action.mp4103.65 MB
  23. 9. Artificial Neural Networks/11. Example 2 - Build Multi-layer perceptron for binary classification.mp4102.28 MB
  24. 11. Deep Learning and Tensorflow Part 2/6. [Activity] Improving our CNN's Topology and with Max Pooling.mp4102.24 MB
  25. 5. Computer Vision Basics Part 2/2. [Activity] Code to perform rotation, translation and resizing.mp4102.05 MB
  26. 4. Computer Vision Basics Part 1/12. Edge Detection and Gradient Calculations (Sobel, Laplace and Canny).mp498.76 MB
  27. 4. Computer Vision Basics Part 1/3. what is an image and how is it digitally stored.mp498.55 MB
  28. 7. Machine Learning Part 1/1. What is Machine Learning.mp496.3 MB
  29. 7. Machine Learning Part 1/6. [Activity] Logistic Regression In Action.mp493.02 MB
  30. 6. Computer Vision Basics Part 3/3. Template Matching - Find a Truck.mp490.26 MB
  31. 5. Computer Vision Basics Part 2/5. Image cropping dilation and erosion.mp487.77 MB
  32. 4. Computer Vision Basics Part 1/4. [Activity] View colored image and convert RGB to Gray.mp486.13 MB
  33. 3. Python Crash Course [Optional]/5. Introduction to Pandas.mp485.99 MB
  34. 3. Python Crash Course [Optional]/6. Introduction to MatPlotLib.mp485.11 MB
  35. 9. Artificial Neural Networks/7. Backpropagation Training.mp484.25 MB
  36. 4. Computer Vision Basics Part 1/10. Convolutions - Sharpening and Blurring.mp484.09 MB
  37. 11. Deep Learning and Tensorflow Part 2/3. [Activity] Classifying Images with a Simple CNN, Part 1.mp483.58 MB
  38. 5. Computer Vision Basics Part 2/8. [Activity] Code to define the region of interest.mp480.31 MB
  39. 6. Computer Vision Basics Part 3/1. Image Features and their importance for object detection.mp479 MB
  40. 8. Machine Learning Part 2/2. [Activity] Naive Bayes in Action.mp478.78 MB
  41. 5. Computer Vision Basics Part 2/6. [Activity] Code to perform Image cropping dilation and erosion.mp476.93 MB
  42. 6. Computer Vision Basics Part 3/5. Corner detection – Harris.mp476.91 MB
  43. 8. Machine Learning Part 2/1. Bayes Theorem and Naive Bayes.mp476.03 MB
  44. 5. Computer Vision Basics Part 2/10. [Activity] Hough transform – practical example in python.mp475.83 MB
  45. 5. Computer Vision Basics Part 2/1. Image Transformation - Rotations, Translation and Resizing.mp475.5 MB
  46. 1. Environment Setup and Installation/1. Introduction.mp474.83 MB
  47. 10. Deep Learning and Tensorflow Part 1/1. Intro to Deep Learning and Tensorflow.mp474.52 MB
  48. 8. Machine Learning Part 2/4. [Activity] Support Vector Classifiers in Action.mp474.35 MB
  49. 9. Artificial Neural Networks/9. Two and Multi-layer Perceptron ANN.mp471.05 MB
  50. 11. Deep Learning and Tensorflow Part 2/1. Convolutional Neural Networks (CNN's).mp470.9 MB
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