Image Processing with Keras in Python

DataCamp

(3)

Course Features

Duration

4 hours

Delivery Method

Online

Available on

Limited Access

Accessibility

Mobile, Desktop, Laptop

Language

English

Subtitles

English

Level

Intermediate

Teaching Type

Self Paced

Video Content

4 hours

Course Description

Deep learning is the use of data to train neural networks for a variety of machine learning tasks, such as classifying objects. Convolutional neural networks are powerful deep learning algorithms that allow image analysis. This course will teach you how to train and evaluate convolutional neural networks. This course will show you how to improve their learning ability using data as well as how to interpret training results.

Course Overview

Virtual Labs

International Faculty

Post Course Interactions

Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Introduction to Deep Learning in Python

What You Will Learn

Learn powerful techniques for image analysis in Python using deep learning and convolutional neural networks in Keras

This course will teach you how to construct, train and evaluate convolutional neural networks

You will also learn how to improve their ability to learn from data, and how to interpret the results of the training

Course Content

Expand all sections

Module 1: Image Processing With Neural Networks

Module 2: Using Convolutions

Module 3: Going Deeper

Module 4: Understanding and Improving Deep Convolutional Networks

Course Instructors

Ariel Rokem

Senior Data Scientist, University of Washington

Ariel Rokem is a Data Scientist at the University of Washington eScience Institute. He received a PhD in neuroscience from UC Berkeley, and postdoctoral training in computational neuroimaging at Stan...

Course Reviews

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