Everything about Convolutional Neural Networks [2022]

Understand everything about CNN (Convolutional Neural Networks) from scratch

You’re looking for a complete Convolutional Neural Network (CNN) course that teaches you everything you need to create an Image Classification model in Python, right?

What you’ll learn

• Get a solid understanding of Convolutional Neural Networks (CNN) and Deep Learning.
• Learn the various Neural Network concepts including Forward Pass, Back propagation, Activation functions etc..
• Learn usage of Keras and Tensorflow libraries.
• Build an end-to-end Image Classification project in Python.
• Use Pandas DataFrames to manipulate data and make statistical computations..
• Completely beginner friendly.

Course Content

• Introduction to CNN –> 2 lectures • 2min.
• Understanding Deep Learning –> 2 lectures • 15min.
• Activation Functions –> 6 lectures • 47min.
• Backpropagation & Gradient Descent –> 2 lectures • 23min.
• More about CNN –> 5 lectures • 1hr 2min.
• Hands-on CNN Practicals –> 2 lectures • 30min.
• Live Project –> 1 lecture • 18min.

Requirements

You’re looking for a complete Convolutional Neural Network (CNN) course that teaches you everything you need to create an Image Classification model in Python, right?

You’ve found the right Convolutional Neural Networks course!

After completing this course you will be able to:

• Identify the Image Classification problems which can be solved using CNN Models.
• Create CNN models in Python using Keras and Tensorflow libraries and analyze their results.
• Confidently practice, discuss and understand Deep Learning concepts
• Have a clear understanding of how Neural Networks work internally, and what are various concepts related to this niche.

How this course will help you?

A Verifiable Certificate of Completion is presented to all students who undertake this Convolutional Neural networks course.

If you are an Analyst or an ML scientist, or a student who wants to learn and apply Deep learning in Real world image recognition problems, this course will give you a solid base for that by teaching you some of the most advanced concepts of Deep Learning and their implementation in Python without getting too Mathematical.

Why should you choose this course?

This course covers all the steps that one should take to create an image classification model using Convolutional Neural Networks.

Most courses only focus on teaching how to run the analysis but we believe that having a strong theoretical understanding of the concepts enables us to create a good model . And after running the analysis, one should be able to judge how good the model is and interpret the results to actually be able to help the business.

Download Practice files

With each lecture, there are class notes attached for you to follow along. There is a final practical assignment for you to practically implement your learning.

What is covered in this course?

• Understanding Deep Learning
• Activation Functions
• How Neural Network works & learns
• Gradient Descent vs Stochastic Gradient Descent
• CNN – Building & Evaluating a model
• Hands-on Project

Go ahead and click the enroll button, and I’ll see you in lesson 1!