The focus of Term 1 is applying machine learning to automotive tasks: deep learning, convolutional neural networks, support vector machines, and computer vision. It includes 5 projects from the Udacity SDC-ND Term 1 curriculum.
GitHub repository links to Term 1 projects are as given below.
1. Lane Lines
To Implement a basic pipeline to find lane lines on the road using Canny edge detector and Hough transforms. Here is the link for the completed project - SDC-P1-Lane-Lines
2. Traffic Sign Classifier
To build a Traffic Sign Recognition Classifier using Neural Network architecture. Here is the link for the completed project - SDC-P2-Traffic-Sign-Classifier
3. Behavioural Cloning
To train Deep Neural Network to learn, how to drive a car using simulator data. Here is the link for the completed project - SDC-P3-Behavioural-Cloning
4. Advanced Lane Finding
This project deals with finding lanes in complex scenarios like curving lines, shadows and changes in the color of the pavement. Here is the link for the completed project - SDC-P4-Advanced-Lane-Finding
5. Vehicle Detection And Tracking
To detect vehicles in an image and track them from frame to frame in a video stream. Here is the link for the completed project - SDC-P5-Vehicle-Detection-And-Tracking