aws-samples/aws-machine-learning-university-accelerated-cv
Machine Learning University: Accelerated Computer Vision Class
| repo name | aws-samples/aws-machine-learning-university-accelerated-cv |
| repo link | https://github.com/aws-samples/aws-machine-learning-university-accelerated-cv |
| homepage | |
| language | Jupyter Notebook |
| size (curr.) | 184724 kB |
| stars (curr.) | 999 |
| created | 2020-07-29 |
| license | Other |
Machine Learning University: Accelerated Computer Vision Class
This repository contains slides, notebooks, and datasets for the Machine Learning University (MLU) Computer Vision class. Our mission is to make Machine Learning accessible to everyone. We have courses available across many topics of machine learning and believe knowledge of ML can be a key enabler for success. This class is designed to help you get started with Computer Vision, learn about widely used Machine Learning techniques and apply them to real-world problems.
YouTube
Watch all Computer Vision class video recordings in this YouTube playlist from our YouTube channel.
Course Overview
There are three lectures and one final project for this class.
| Lecture 1 | Lecture 2 | Lecture 3 |
|---|---|---|
| Intro to ML | Image Datasets | Advanced CNNs: VGGNet and ResNet |
| Intro to Computer Vision | Training Neural Networks | Object Detection |
| Neural Networks | Modern CNNs: LeNet and AlexNet | Semantic Segmentation |
| Convolutional Neural Networks | Model fine-tuning |
Final Project: Practice working with a “real-world” computer vision dataset for the final project. Final project dataset is in the data/final_project_dataset folder. For more details on the final project, check out this notebook.
Contribute
If you would like to contribute to the project, see CONTRIBUTING for more information.
License
The license for this repository depends on the section. Data set for the course is being provided to you by permission of Amazon and is subject to the terms of the Amazon License and Access. You are expressly prohibited from copying, modifying, selling, exporting or using this data set in any way other than for the purpose of completing this course. The lecture slides are released under the CC-BY-SA-4.0 License. The code examples are released under the MIT-0 License. See each section’s LICENSE file for details.
