Autonomous Cars: Deep Learning and Computer Vision in Python

Learn OpenCV, Keras, object and lane detection, and traffic sign classification for self-driving cars
4.50 (1379 reviews)
Udemy
platform
English
language
Software Engineering
category
Sundog Education by Fran
instructor
Autonomous Cars: Deep Learning and Computer Vision in Python
12,417
students
12.5 hours
content
Aug 2024
last update
$79.99
regular price

What you will learn

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

Screenshots

Autonomous Cars: Deep Learning and Computer Vision in Python - Screenshot_01Autonomous Cars: Deep Learning and Computer Vision in Python - Screenshot_02Autonomous Cars: Deep Learning and Computer Vision in Python - Screenshot_03Autonomous Cars: Deep Learning and Computer Vision in Python - Screenshot_04
Related Topics
1909224
udemy ID
9/12/2018
course created date
8/5/2019
course indexed date
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