Fundamentals of Convolutional Neural Network (CNN)
What you'll learn
- Classify images using Convolutional Neural Network (CNN)
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.
Who this course is for:
- Beginner Python developers who are curious about data science
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 22,000 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.