Implement Image Captioning with Recurrent Neural Networks

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Abdul Rehman Yousaf

1:25:45

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1. Course Overview

1. Course Overview.mp4

01:49

2. Introducing Image Captioning

1. Overview.mp4

02:58

2. What Is Image Captioning and Why Is It Important.mp4

03:26

3. Introducing the Business Case Study for Image-captioning.mp4

02:19

4. Proposed Solutions for Image Captioning Case Study.mp4

06:13

5. Summary.mp4

01:01

3. Preparing Data for Image Captioning Models

1. Module and Project Overview.mp4

07:40

2. Demo - Load and Explore the Dataset.mp4

10:21

3. Demo - Pre-processing the Images Data.mp4

07:43

4. Demo - Pre-processing the Captions Data.mp4

06:32

5. Demo - Prepare Training Data Using Pre-processed Data.mp4

03:50

6. Summary.mp4

00:51

4. Building the Model for Image Captioning Using Tensorflow

1. Overview.mp4

01:10

3. Demo - Implement CNN Encoder in TensorFlow.mp4

01:16

5. Demo - Define the Loss Function and Model Checkpoints.mp4

02:46

6. Demo - Perform Model Training.mp4

03:26

7. Demo - Making Predictions out of the Trained Model.mp4

01:35

8. Summary.mp4

00:48

5. Evaluating Deep Learning Models for Image Captioning

1. Overview.mp4

00:59

2. Meshed Memory Transformer for Image Captioning.mp4

03:44

3. Evaluation Metrics for Image Captioning.mp4

10:16

4. Bottom-up and Top-down Attention for Image Captioning.mp4

02:34

5. Summary.mp4

02:28

Description

This course will teach you how to build and train image captioning models using TensorFlow, with the help of a case study - building a model for image tagging. You will learn how to prepare the data for model training and evaluate the trained model.

What You'll Learn?

Manually interpreting billions of images is time-consuming and almost impossible. But if we teach machines to understand images, this task will become much more efficient. In this course, Implement Image Captioning with Recurrent Neural Networks, you’ll learn to build and train image captioning models with RNNs using TensorFlow. First, you’ll explore the broader understanding of recurrent neural networks along with an overview of image captioning and how CNNs can help us to understand images. Next, you’ll discover how to prepare image and text data. Then, you'll learn how to develop a deep learning model for image captioning, and different options to evaluate that model using TensorFlow. Finally, you’ll understand the implementation of the data science process. When you’re finished with this course, you’ll have the skills and knowledge of RNNs and CNNs needed to build image captioning models.

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TensorFlow

Neural Networks

Abdul Rehman Yousaf

Instructor's Courses

Abdul Rehman is the founder of Pythonist.org, a software consulting, training, and application development company. Currently, he is working as a Senior Machine Learning Engineer at Nexthon Technologies where he built several amazing projects powered with artificial intelligence. Prior to that, he worked as a Cloud Solution Architect, building powerful, secure, and scalable infrastructures on various cloud vendors like Google Cloud Platform and AWS. During both of these roles, he used Python as the core language for his development. He is an experienced presenter and teacher, having spoken at several conferences, software groups, and internal corporate venues. Abdul is also an active member of the open-source community, contributing regularly to various Python and Machine Learning related projects. Abdul holds a Bachelor's degree in Information Technology from the University of Gujrat Pakistan.

Pluralsight

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Pluralsight, LLC is an American privately held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 7,000 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.