Ementorhub

What you'll learn

Describe the applications of computer vision across different industries.

Apply image processing and analysis techniques to computer vision problems.

Utilize Python, Pillow, and OpenCV for basic image processing and perform image classification and object detection.

Create an image classifier using Supervised learning techniques.

Skills you'll gain

Computer Vision

Machine Learning

Tensorflow

Keras (Neural Network Library)

Data Processing

Computer Programming

Visualization (Computer Graphics)

Artificial Intelligence and Machine Learning (AI/ML)

Artificial Neural Networks

IBM Cloud

Deep Learning

Cloud Applications

Image Analysis

PyTorch (Machine Learning Library)

Application Deployment

Augmented Reality

There are 6 modules in this course

As part of this course, you will utilize Python, Pillow, and OpenCV for basic image processing and perform image classification and object detection. This is a hands-on course and involves several labs and exercises. Labs will combine Jupyter Labs and Computer Vision Learning Studio (CV Studio), a free learning tool for computer vision. CV Studio allows you to upload, train, and test your own custom image classifier and detection models. At the end of the course, you will create your own computer vision web app and deploy it to the Cloud. This course does not require any prior Machine Learning or Computer Vision experience. However, some knowledge of the Python programming language and high school math is necessary.

Image Processing with OpenCV and Pillow

Machine Learning Image Classification

Neural Networks and Deep Learning for Image Classification

Object Detection

Project Case: Not Quite a Self-Driving Car - Traffic Sign Classification