Deep Learning with Caffe

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Pratheerth Padman

1:07:30

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01. Course Overview

01. Course Overview.mp4

01:46

02. Demystifying Deep Learning and Image Classification

02. Course and Module Introduction.mp4

02:14

03. What Is Deep Learning.mp4

03:59

04. Basics of a Neural Network.mp4

02:06

05. Working of a Neural Network.mp4

02:55

06. Gradient Descent.mp4

03:40

07. Image Classification - Overview and Applications.mp4

01:48

08. Demo-Installing the Required Libraries.mp4

02:02

09. Summary.mp4

01:01

03. Building a Convolutional Neural Network to Classify Images

10. Module Introduction.mp4

00:46

11. Basics of Computer Vision.mp4

02:19

12. What Are Convolutional Neural Networks.mp4

01:04

13. CNN-Convolutions.mp4

04:26

14. CNN-Activation and Pooling.mp4

03:24

15. CNN-Classification.mp4

01:01

16. Demo-Introduction to the Dataset .mp4

03:08

17. What Is Caffe.mp4

01:03

18. Demo-Data Preparation.mp4

05:00

19. Demo-Model Definition.mp4

04:53

20. Demo-Solver Definition.mp4

01:59

21. Demo-Training and Prediction Using the Model .mp4

02:13

22. Summary.mp4

01:24

04. Improving Performance Using Transfer Learning

23. Module Introduction.mp4

00:50

24. Better Performance - Why and How.mp4

01:50

25. What Is Transfer Learning.mp4

03:50

26. Transfer Learning - Use Case Scenarios.mp4

03:53

27. Demo-Improving Model Performance Using Transfer Learning.mp4

01:52

28. Summary and Feedback.mp4

01:04

Description

This course will teach you to build your very own convolutional neural network with Caffe to solve custom image classification problems.

What You'll Learn?

There are many deep learning frameworks to choose from. Caffe, which is written with speed, expression, and modularity in mind, is a great contender to be your framework of choice. In this course, Deep Learning with Caffe, you’ll learn to use Caffe to build a convolutional neural network that will help you classify a given set of images.

First, you’ll explore what deep learning is, how it differs from traditional machine learning, and how a neural network functions. Next, while building your very own convolutional neural network, you’ll learn how to prepare data for deep learning, define the model and solver, and train the model. Finally, you’ll discover how to improve the performance of your model using transfer learning.

When you’re finished with this course, you’ll have the skills and knowledge necessary to build your very own CNN using Caffe that’ll help solve custom image classification problems.

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Machine Learning

Deep Learning

Pratheerth Padman

Instructor's Courses

Pratheerth is a Data Scientist who has entered the field after an eclectic mix of educational and work experiences. He has a Bachelor's in Engineering in Mechatronics from India, Masters in Engineering Management from Australia and then a couple of years of work experience as a Production Engineer in the Middle East. Then when the A.I bug bit him, he dropped everything to dedicate his life to the field. He is currently working on mentoring, course creation and freelancing as a Data Scientist.

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.