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