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

Creation Time	March 19, 2025, 3:13 p.m.
Last Access Time	March 20, 2025, 1:52 a.m.
File Size	7.4 GB
Keywords	and FreeCourseSite Python Cars - Deep Udemy Computer Learning in Autonomous com Vision
Total Requests	2
Total Files	188
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9. Artificial Neural Networks/10. Example 1 - Build Multi-layer perceptron for binary classification.mp4 384.2 MB
8. Machine Learning Part 2/6. [Activity] Detecting Cars Using SVM - Part #2.mp4 204.1 MB
11. Deep Learning and Tensorflow Part 2/8. [Activity] Build a CNN to Classify Traffic Siigns - part 2.mp4 175.3 MB
6. Computer Vision Basics Part 3/11. Histogram of Oriented Gradients (HOG).mp4 169.5 MB
4. Computer Vision Basics Part 1/9. [Activity] Convert RGB to HSV color spaces and mergesplit channels.mp4 166.9 MB
9. Artificial Neural Networks/4. ANN Training and dataset split.mp4 151.3 MB
11. Deep Learning and Tensorflow Part 2/7. [Activity] Build a CNN to Classify Traffic Signs.mp4 150.6 MB
3. Python Crash Course [Optional]/7. Introduction to Seaborn.mp4 146.7 MB
2. Introduction to Self-Driving Cars/1. A Brief History of Autonomous Vehicles.mp4 145.9 MB
5. Computer Vision Basics Part 2/9. Hough transform theory.mp4 141.5 MB
4. Computer Vision Basics Part 1/2. Humans vs. Computers Vision system.mp4 135.3 MB
10. Deep Learning and Tensorflow Part 1/3. [Activity] Building a Logistic Classifier with Deep Learning and Keras.mp4 134.6 MB
9. Artificial Neural Networks/1. Introduction What are Artificial Neural Networks and how do they learn.mp4 127.8 MB
8. Machine Learning Part 2/5. Project Solution Detecting Cars Using SVM - Part #1.mp4 119.7 MB
9. Artificial Neural Networks/2. Single Neuron Perceptron Model.mp4 119.7 MB
4. Computer Vision Basics Part 1/1. What is computer vision and why is it important.mp4 118.8 MB
5. Computer Vision Basics Part 2/11. Project Solution Hough transform to detect lane lines in an image.mp4 117.0 MB
8. Machine Learning Part 2/7. [Activity] Project Solution Detecting Cars Using SVM - Part #3.mp4 116.8 MB
4. Computer Vision Basics Part 1/8. Color Spaces.mp4 113.7 MB
9. Artificial Neural Networks/6. Code to build a perceptron for binary classification.mp4 111.6 MB
9. Artificial Neural Networks/8. Code to Train a perceptron for binary classification.mp4 110.2 MB
7. Machine Learning Part 1/8. [Activity] Decision Trees In Action.mp4 103.7 MB
9. Artificial Neural Networks/11. Example 2 - Build Multi-layer perceptron for binary classification.mp4 102.3 MB
11. Deep Learning and Tensorflow Part 2/6. [Activity] Improving our CNN's Topology and with Max Pooling.mp4 102.2 MB
5. Computer Vision Basics Part 2/2. [Activity] Code to perform rotation, translation and resizing.mp4 102.1 MB
4. Computer Vision Basics Part 1/12. Edge Detection and Gradient Calculations (Sobel, Laplace and Canny).mp4 98.8 MB
4. Computer Vision Basics Part 1/3. what is an image and how is it digitally stored.mp4 98.5 MB
7. Machine Learning Part 1/1. What is Machine Learning.mp4 96.3 MB
7. Machine Learning Part 1/6. [Activity] Logistic Regression In Action.mp4 93.0 MB
6. Computer Vision Basics Part 3/3. Template Matching - Find a Truck.mp4 90.3 MB
5. Computer Vision Basics Part 2/5. Image cropping dilation and erosion.mp4 87.8 MB
4. Computer Vision Basics Part 1/4. [Activity] View colored image and convert RGB to Gray.mp4 86.1 MB
3. Python Crash Course [Optional]/5. Introduction to Pandas.mp4 86.0 MB
3. Python Crash Course [Optional]/6. Introduction to MatPlotLib.mp4 85.1 MB
9. Artificial Neural Networks/7. Backpropagation Training.mp4 84.2 MB
4. Computer Vision Basics Part 1/10. Convolutions - Sharpening and Blurring.mp4 84.1 MB
11. Deep Learning and Tensorflow Part 2/3. [Activity] Classifying Images with a Simple CNN, Part 1.mp4 83.6 MB
5. Computer Vision Basics Part 2/8. [Activity] Code to define the region of interest.mp4 80.3 MB
6. Computer Vision Basics Part 3/1. Image Features and their importance for object detection.mp4 79.0 MB
8. Machine Learning Part 2/2. [Activity] Naive Bayes in Action.mp4 78.8 MB
5. Computer Vision Basics Part 2/6. [Activity] Code to perform Image cropping dilation and erosion.mp4 76.9 MB
6. Computer Vision Basics Part 3/5. Corner detection – Harris.mp4 76.9 MB
8. Machine Learning Part 2/1. Bayes Theorem and Naive Bayes.mp4 76.0 MB
5. Computer Vision Basics Part 2/10. [Activity] Hough transform – practical example in python.mp4 75.8 MB
5. Computer Vision Basics Part 2/1. Image Transformation - Rotations, Translation and Resizing.mp4 75.5 MB
1. Environment Setup and Installation/1. Introduction.mp4 74.8 MB
10. Deep Learning and Tensorflow Part 1/1. Intro to Deep Learning and Tensorflow.mp4 74.5 MB
8. Machine Learning Part 2/4. [Activity] Support Vector Classifiers in Action.mp4 74.3 MB
9. Artificial Neural Networks/9. Two and Multi-layer Perceptron ANN.mp4 71.0 MB
11. Deep Learning and Tensorflow Part 2/1. Convolutional Neural Networks (CNN's).mp4 70.9 MB
5. Computer Vision Basics Part 2/4. [Activity] Perform non-affine image transformation on a traffic sign image.mp4 68.6 MB
3. Python Crash Course [Optional]/1. Python Basics Whitespace, Imports, and Lists.mp4 68.2 MB
4. Computer Vision Basics Part 1/14. [Activity] Project #1 Canny Sobel and Laplace Edge Detection using Webcam.mp4 67.5 MB
9. Artificial Neural Networks/5. Practical Example - Vehicle Speed Determination.mp4 67.5 MB
11. Deep Learning and Tensorflow Part 2/4. [Activity] Classifying Images with a Simple CNN, Part 2.mp4 67.1 MB
4. Computer Vision Basics Part 1/11. [Activity] Convolutions - Sharpening and Blurring.mp4 66.1 MB
7. Machine Learning Part 1/2. Evaluating Machine Learning Systems with Cross-Validation.mp4 66.0 MB
10. Deep Learning and Tensorflow Part 1/2. Building Deep Neural Networks with Keras, Normalization, and One-Hot Encoding..mp4 63.9 MB
4. Computer Vision Basics Part 1/7. What are the challenges of color selection technique.mp4 62.5 MB
7. Machine Learning Part 1/7. Decision Trees and Random Forests.mp4 61.5 MB
1. Environment Setup and Installation/2. Install Anaconda, OpenCV, Tensorflow, and the Course Materials.mp4 61.5 MB
1. Environment Setup and Installation/3. Test your Environment with Real-Time Edge Detection in a Jupyter Notebook.mp4 61.3 MB
6. Computer Vision Basics Part 3/12. [Activity] Code to perform HOG Feature extraction.mp4 61.0 MB
5. Computer Vision Basics Part 2/3. Image Transformations – Perspective transform.mp4 59.7 MB
6. Computer Vision Basics Part 3/7. Image Scaling – Pyramiding updown.mp4 57.5 MB
6. Computer Vision Basics Part 3/6. [Activity] Code to perform corner detection.mp4 57.1 MB
4. Computer Vision Basics Part 1/13. [Activity] Edge Detection and Gradient Calculations (Sobel, Laplace and Canny).mp4 52.6 MB
5. Computer Vision Basics Part 2/7. Region of interest masking.mp4 51.9 MB
4. Computer Vision Basics Part 1/5. [Activity] Detect lane lines in gray scale image.mp4 47.3 MB
10. Deep Learning and Tensorflow Part 1/4. ReLU Activation, and Preventing Overfitting with Dropout Regularlization.mp4 43.6 MB
9. Artificial Neural Networks/3. Activation Functions.mp4 42.5 MB
6. Computer Vision Basics Part 3/2. [Activity] Find a truck in an image manually!.mp4 42.5 MB
6. Computer Vision Basics Part 3/13. Feature Extraction - SIFT, SURF, FAST and ORB.mp4 42.4 MB
11. Deep Learning and Tensorflow Part 2/2. Implementing CNN's in Keras.mp4 42.3 MB
6. Computer Vision Basics Part 3/4. [Activity] Project Solution Find a Truck Using Template Matching.mp4 41.5 MB
10. Deep Learning and Tensorflow Part 1/5. [Activity] Improving our Classifier with Dropout Regularization.mp4 41.4 MB
7. Machine Learning Part 1/4. [Activity] Linear Regression in Action.mp4 41.2 MB
6. Computer Vision Basics Part 3/10. [Activity] Code to obtain color histogram.mp4 40.4 MB
8. Machine Learning Part 2/3. Support Vector Machines (SVM) and Support Vector Classifiers (SVC).mp4 40.2 MB
7. Machine Learning Part 1/3. Linear Regression.mp4 35.9 MB
4. Computer Vision Basics Part 1/6. [Activity] Detect lane lines in colored image.mp4 33.8 MB
6. Computer Vision Basics Part 3/14. [Activity] FASTORB Feature Extraction in OpenCV.mp4 33.8 MB
6. Computer Vision Basics Part 3/9. Histogram of colors.mp4 32.9 MB
3. Python Crash Course [Optional]/2. Python Basics Tuples and Dictionaries.mp4 30.8 MB
6. Computer Vision Basics Part 3/8. [Activity] Code to perform Image pyramiding.mp4 29.2 MB
3. Python Crash Course [Optional]/3. Python Basics Functions and Boolean Operations.mp4 27.2 MB
12. Wrapping Up/1. Bonus Lecture Keep Learning with Sundog Education.mp4 22.2 MB
1. Environment Setup and Installation/4. Udemy 101 Getting the Most From This Course.mp4 19.7 MB
3. Python Crash Course [Optional]/4. Python Basics Looping and an Exercise.mp4 19.1 MB
2. Introduction to Self-Driving Cars/2. Course Overview and Learning Outcomes.mp4 14.5 MB
7. Machine Learning Part 1/5. Logistic Regression.mp4 11.4 MB
11. Deep Learning and Tensorflow Part 2/5. Max Pooling.mp4 8.5 MB
9. Artificial Neural Networks/10. Example 1 - Build Multi-layer perceptron for binary classification.vtt 54.9 KB
11. Deep Learning and Tensorflow Part 2/8. [Activity] Build a CNN to Classify Traffic Siigns - part 2.vtt 25.9 KB
3. Python Crash Course [Optional]/7. Introduction to Seaborn.vtt 25.5 KB
8. Machine Learning Part 2/6. [Activity] Detecting Cars Using SVM - Part #2.vtt 23.8 KB
4. Computer Vision Basics Part 1/9. [Activity] Convert RGB to HSV color spaces and mergesplit channels.vtt 20.8 KB
10. Deep Learning and Tensorflow Part 1/3. [Activity] Building a Logistic Classifier with Deep Learning and Keras.vtt 20.7 KB
9. Artificial Neural Networks/4. ANN Training and dataset split.vtt 20.4 KB
7. Machine Learning Part 1/8. [Activity] Decision Trees In Action.vtt 19.7 KB
9. Artificial Neural Networks/2. Single Neuron Perceptron Model.vtt 19.1 KB
3. Python Crash Course [Optional]/6. Introduction to MatPlotLib.vtt 19.1 KB
5. Computer Vision Basics Part 2/9. Hough transform theory.vtt 19.0 KB
6. Computer Vision Basics Part 3/11. Histogram of Oriented Gradients (HOG).vtt 17.8 KB
9. Artificial Neural Networks/1. Introduction What are Artificial Neural Networks and how do they learn.vtt 17.7 KB
3. Python Crash Course [Optional]/5. Introduction to Pandas.vtt 17.3 KB
11. Deep Learning and Tensorflow Part 2/7. [Activity] Build a CNN to Classify Traffic Signs.vtt 17.2 KB
2. Introduction to Self-Driving Cars/1. A Brief History of Autonomous Vehicles.vtt 17.2 KB
5. Computer Vision Basics Part 2/11. Project Solution Hough transform to detect lane lines in an image.vtt 16.8 KB
9. Artificial Neural Networks/8. Code to Train a perceptron for binary classification.vtt 16.0 KB
10. Deep Learning and Tensorflow Part 1/2. Building Deep Neural Networks with Keras, Normalization, and One-Hot Encoding..vtt 15.6 KB
3. Python Crash Course [Optional]/1. Python Basics Whitespace, Imports, and Lists.vtt 15.6 KB
7. Machine Learning Part 1/2. Evaluating Machine Learning Systems with Cross-Validation.vtt 15.6 KB
4. Computer Vision Basics Part 1/2. Humans vs. Computers Vision system.vtt 15.3 KB
9. Artificial Neural Networks/6. Code to build a perceptron for binary classification.vtt 15.1 KB
4. Computer Vision Basics Part 1/12. Edge Detection and Gradient Calculations (Sobel, Laplace and Canny).vtt 14.7 KB
7. Machine Learning Part 1/6. [Activity] Logistic Regression In Action.vtt 14.6 KB
10. Deep Learning and Tensorflow Part 1/1. Intro to Deep Learning and Tensorflow.vtt 14.6 KB
11. Deep Learning and Tensorflow Part 2/6. [Activity] Improving our CNN's Topology and with Max Pooling.vtt 14.6 KB
8. Machine Learning Part 2/5. Project Solution Detecting Cars Using SVM - Part #1.vtt 14.2 KB
4. Computer Vision Basics Part 1/8. Color Spaces.vtt 14.2 KB
8. Machine Learning Part 2/1. Bayes Theorem and Naive Bayes.vtt 14.1 KB
7. Machine Learning Part 1/1. What is Machine Learning.vtt 14.0 KB
7. Machine Learning Part 1/7. Decision Trees and Random Forests.vtt 13.7 KB
5. Computer Vision Basics Part 2/2. [Activity] Code to perform rotation, translation and resizing.vtt 13.6 KB
8. Machine Learning Part 2/2. [Activity] Naive Bayes in Action.vtt 13.5 KB
4. Computer Vision Basics Part 1/1. What is computer vision and why is it important.vtt 13.0 KB
9. Artificial Neural Networks/11. Example 2 - Build Multi-layer perceptron for binary classification.vtt 13.0 KB
4. Computer Vision Basics Part 1/4. [Activity] View colored image and convert RGB to Gray.vtt 13.0 KB
8. Machine Learning Part 2/7. [Activity] Project Solution Detecting Cars Using SVM - Part #3.vtt 12.2 KB
4. Computer Vision Basics Part 1/3. what is an image and how is it digitally stored.vtt 12.0 KB
8. Machine Learning Part 2/4. [Activity] Support Vector Classifiers in Action.vtt 11.7 KB
9. Artificial Neural Networks/7. Backpropagation Training.vtt 11.3 KB
11. Deep Learning and Tensorflow Part 2/3. [Activity] Classifying Images with a Simple CNN, Part 1.vtt 11.2 KB
11. Deep Learning and Tensorflow Part 2/4. [Activity] Classifying Images with a Simple CNN, Part 2.vtt 11.2 KB
4. Computer Vision Basics Part 1/10. Convolutions - Sharpening and Blurring.vtt 10.9 KB
5. Computer Vision Basics Part 2/8. [Activity] Code to define the region of interest.vtt 10.7 KB
5. Computer Vision Basics Part 2/10. [Activity] Hough transform – practical example in python.vtt 10.3 KB
9. Artificial Neural Networks/9. Two and Multi-layer Perceptron ANN.vtt 10.1 KB
5. Computer Vision Basics Part 2/5. Image cropping dilation and erosion.vtt 9.8 KB
11. Deep Learning and Tensorflow Part 2/1. Convolutional Neural Networks (CNN's).vtt 9.7 KB
8. Machine Learning Part 2/3. Support Vector Machines (SVM) and Support Vector Classifiers (SVC).vtt 9.6 KB
5. Computer Vision Basics Part 2/6. [Activity] Code to perform Image cropping dilation and erosion.vtt 9.4 KB
10. Deep Learning and Tensorflow Part 1/4. ReLU Activation, and Preventing Overfitting with Dropout Regularlization.vtt 9.3 KB
9. Artificial Neural Networks/5. Practical Example - Vehicle Speed Determination.vtt 9.2 KB
5. Computer Vision Basics Part 2/4. [Activity] Perform non-affine image transformation on a traffic sign image.vtt 9.1 KB
6. Computer Vision Basics Part 3/3. Template Matching - Find a Truck.vtt 8.9 KB
7. Machine Learning Part 1/4. [Activity] Linear Regression in Action.vtt 8.9 KB
11. Deep Learning and Tensorflow Part 2/2. Implementing CNN's in Keras.vtt 8.8 KB
4. Computer Vision Basics Part 1/11. [Activity] Convolutions - Sharpening and Blurring.vtt 8.8 KB
3. Python Crash Course [Optional]/2. Python Basics Tuples and Dictionaries.vtt 8.7 KB
7. Machine Learning Part 1/3. Linear Regression.vtt 8.7 KB
1. Environment Setup and Installation/3. Test your Environment with Real-Time Edge Detection in a Jupyter Notebook.vtt 8.6 KB
5. Computer Vision Basics Part 2/1. Image Transformation - Rotations, Translation and Resizing.vtt 8.5 KB
6. Computer Vision Basics Part 3/5. Corner detection – Harris.vtt 8.3 KB
4. Computer Vision Basics Part 1/14. [Activity] Project #1 Canny Sobel and Laplace Edge Detection using Webcam.vtt 8.2 KB
3. Python Crash Course [Optional]/3. Python Basics Functions and Boolean Operations.vtt 8.2 KB
6. Computer Vision Basics Part 3/1. Image Features and their importance for object detection.vtt 7.7 KB
3. Python Crash Course [Optional]/4. Python Basics Looping and an Exercise.vtt 7.3 KB
4. Computer Vision Basics Part 1/5. [Activity] Detect lane lines in gray scale image.vtt 7.2 KB
6. Computer Vision Basics Part 3/6. [Activity] Code to perform corner detection.vtt 7.2 KB
1. Environment Setup and Installation/2. Install Anaconda, OpenCV, Tensorflow, and the Course Materials.vtt 7.1 KB
5. Computer Vision Basics Part 2/7. Region of interest masking.vtt 7.0 KB
5. Computer Vision Basics Part 2/3. Image Transformations – Perspective transform.vtt 6.9 KB
4. Computer Vision Basics Part 1/13. [Activity] Edge Detection and Gradient Calculations (Sobel, Laplace and Canny).vtt 6.7 KB
9. Artificial Neural Networks/3. Activation Functions.vtt 6.4 KB
10. Deep Learning and Tensorflow Part 1/5. [Activity] Improving our Classifier with Dropout Regularization.vtt 6.3 KB
6. Computer Vision Basics Part 3/12. [Activity] Code to perform HOG Feature extraction.vtt 6.1 KB
4. Computer Vision Basics Part 1/7. What are the challenges of color selection technique.vtt 5.4 KB
4. Computer Vision Basics Part 1/6. [Activity] Detect lane lines in colored image.vtt 5.2 KB
6. Computer Vision Basics Part 3/7. Image Scaling – Pyramiding updown.vtt 5.2 KB
6. Computer Vision Basics Part 3/10. [Activity] Code to obtain color histogram.vtt 5.2 KB
6. Computer Vision Basics Part 3/4. [Activity] Project Solution Find a Truck Using Template Matching.vtt 5.0 KB
2. Introduction to Self-Driving Cars/2. Course Overview and Learning Outcomes.vtt 5.0 KB
6. Computer Vision Basics Part 3/2. [Activity] Find a truck in an image manually!.vtt 4.8 KB
7. Machine Learning Part 1/5. Logistic Regression.vtt 4.6 KB
1. Environment Setup and Installation/1. Introduction.vtt 4.1 KB
6. Computer Vision Basics Part 3/13. Feature Extraction - SIFT, SURF, FAST and ORB.vtt 4.0 KB
6. Computer Vision Basics Part 3/14. [Activity] FASTORB Feature Extraction in OpenCV.vtt 4.0 KB
11. Deep Learning and Tensorflow Part 2/5. Max Pooling.vtt 3.9 KB
1. Environment Setup and Installation/4. Udemy 101 Getting the Most From This Course.vtt 3.5 KB
6. Computer Vision Basics Part 3/8. [Activity] Code to perform Image pyramiding.vtt 3.2 KB
6. Computer Vision Basics Part 3/9. Histogram of colors.vtt 3.1 KB
12. Wrapping Up/1. Bonus Lecture Keep Learning with Sundog Education.vtt 1.8 KB
0. Websites you may like/[FCS Forum].url 133 bytes
0. Websites you may like/[FreeCourseSite.com].url 127 bytes
0. Websites you may like/[CourseClub.ME].url 122 bytes
1. Environment Setup and Installation/2.1 Course materials page.html 102 bytes

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