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Convolutional Neural Network

person icon Evergreen Technologies

Convolutional Neural Network

Classify images using Convolutional Neural Network (CNN)

updated on icon Updated on Sep, 2023

language icon Language - English

person icon Evergreen Technologies

architecture icon Development,Data Science,Deep Learning

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Course Description

Course Description

Learn to build image classification  engine with using Convolutional Neural Network (CNN) .  CNN is popular network where a machine can be trained to classify images based on patterns in the images.  Once trained, it can be used to identify objects in the images.

A lot of smart researchers have already spent lot of time building really good image classification networks like VGGNET, RESNET, Inception V3. The networks are variants of CNN. These networks have been trained on imagenet animal dataset. If your dataset requires a different type of image classification, you could just start with these networks and fine tune them on your smaller dataset. This saves significant time and resources.

Build a strong foundation in CNN  with this tutorial for beginners.

  • Understanding fundamentals Convolution

  • Understanding fundamentals of deep learning and CNN

  • Benefits of CNN

  • Learn how to apply CNN with real example

  • Use Jupyter Notebook for step by step programming

  • Fine tune accuracy of CNN

  • Build a real life web application for dog  vs cats classification

  • A Powerful Skill at Your Fingertips  Learning the fundamentals of CNN  puts a powerful and very useful tool at your fingertips. Python and Jupyter are free, easy to learn, has excellent documentation.

No prior knowledge of CNN or deep learning is assumed. I'll be covering topics like deep learning, Convolution and CNN   from scratch. 

Jobs in computer vision area are plentiful, and being able to learn transfer learning will give you a strong edge. CNN is  state of art technology that can quickly help you achieve your goal. 

Learning image classification with CNN will help you become a computer vision developer which is in high demand.

Content and Overview  

This course teaches you on how to build dog vs cats classification engine using open source Python and Jupyter framework.  You will work along with me step by step to build following answers

  • Introduction to Convolution

  • Introduction to CNN

  • Build an jupyter notebook step by step using CNN 

  • Build a real world web application to find cat vs dog

What am I going to get from this course?

  • Learn CNN and build dog vs cats image classification engine from professional trainer from your own desk.

  • Over 10 lectures teaching you how to build image classification engine

  • Suitable for beginner programmers and ideal for users who learn faster when shown.

  • Visual training method, offering users increased retention and accelerated learning.

  • Breaks even the most complex applications down into simplistic steps.

  • Offers challenges to students to enable reinforcement of concepts. Also solutions are described to validate the challenges.

Goals

What will you learn in this course:

  • Classify images using Convolutional Neural Network (CNN)

Prerequisites

What are the prerequisites for this course?

  • None

Convolutional Neural Network

Curriculum

Check out the detailed breakdown of what’s inside the course

Introduction
3 Lectures
  • play icon Introduction 08:08 08:08
  • play icon Source Code Structure 05:06 05:06
  • play icon About Author 05:42 05:42
Set up
2 Lectures
Tutorialspoint
Basics of Convolution
4 Lectures
Tutorialspoint
CNN and deep learning fundamentals
2 Lectures
Tutorialspoint
Model Training
2 Lectures
Tutorialspoint
Building Web Application
2 Lectures
Tutorialspoint

Instructor Details

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Evergreen Technologies

Over 20 years of experience in  programming applications in Fortune 500 companies. I have written 2 books on software design patterns and performance tuning that are published on kindle, nook and ibooks.  So far I have taught react.js, nunit, Chatbot , several courses on machine learning and design patterns.  I have also been working in machine learning area for many years. My passion is leverage my years of experience to teach students in a intuitive and enjoyable manner. 

I spent many years at fortune 500 companies, developing and managing the technology that automatically delivers SaaS applications to hundreds of millions of customers.  I have started my own successful company, Evergreen Technologies in 2019, which focuses on online education. 

I have over 8000 students spread over 145 countries on Udemy. 

I am also available for technical consultation, resume screening and conducting technical interviews of candidates to expedite hiring.

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