Computer Vision
Offered By: Nvidia Deep Learning Institute via Udacity
Course Description
Overview
Master the computer vision skills behind advances in robotics and automation. Write programs to analyze images, implement feature extraction, and recognize objects using deep learning models.
Syllabus
- Welcome to the Nanodegree Program!
- Welcome to Udacity! We're excited to share more about your Nanodegree program and start this journey with you!
- Introduction to Computer Vision
- Master computer vision and image processing essentials. Learn to extract important features from image
data, and apply deep learning techniques to classification tasks - Optional: Cloud Computing
- Advanced Computer Vision and Deep Learning
- Learn to apply deep learning architectures to computer vision tasks. Discover how to combine CNN and RNN networks to build an automatic image captioning application.
- Object Tracking and Localization
- Learn how to locate an object and track it over time. These techniques are used in a variety of moving systems, such as self-driving car navigation and drone flight.
- Applications of Computer Vision & Deep Learning
- Take a quick look at a few really cool applications of deep learning and computer vision, such as Neural Style Transfer, that using pre-trained models.
- Review: Training A Neural Network
- Review how neural networks turn an input into an output and how they monitor errors as they train. This section will also cover methods to avoid overfitting your data.
- Skin Cancer Detection
- Learn how to utilize neural networks to distinguish between images of benign and cancerous skin tissue.
- Text Sentiment Analysis
- Learn how to create a simple neural network for analyzing the sentiment (bad or good) in the text of movie reviews.
- More Deep Learning Models
- C++ Programming
- Career Services
Taught by
Sebastian Thrun, Cezanne Camacho, Alexis Cook, Juan Delgado, Jay Alammar, Ortal Arel, Luis Serrano, Pranjal C., Arunava C., Christopher O., Ramy Raafat Mohamed Fawzy Ahmed W., Akira K. and Keelia T.
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