What you’ll learn
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Automatically detect lane markings in images
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Detect cars and pedestrians using a trained classifier and with SVM
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Classify traffic signs using Convolutional Neural Networks
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Identify other vehicles in images using template matching
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Build deep neural networks with Tensorflow and Keras
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Analyze and visualize data with Numpy, Pandas, Matplotlib, and Seaborn
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Process image data using OpenCV
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Calibrate cameras in Python, correcting for distortion
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Sharpen and blur images with convolution
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Detect edges in images with Sobel, Laplace, and Canny
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Transform images through translation, rotation, resizing, and perspective transform
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Extract image features with HOG
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Detect object corners with Harris
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Classify data with machine learning techniques including regression, decision trees, Naive Bayes, and SVM
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Classify data with artificial neural networks and deep learning
Deal Score0
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