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CNN for Computer Vision with Keras and TensorFlow in Python

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CNN for Computer Vision with Keras and TensorFlow in Python

21 Nov , 2020  

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Requirements
Students will need to install Python and Anaconda software but we have a separate lecture to help you install the sameStudents will need to install Python and Anaconda software but we have a separate lecture to help you install the same

Description
You’re looking for a complete Convolutional Neural Network (CNN) course that teaches you everything you need to create a Image Recognition 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 Recognition 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 Advanced Image Recognition models such as LeNet, GoogleNet, VGG16 etc.

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 recognition 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.

What makes us qualified to teach you?

The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using Deep learning techniques and we have used our experience to include the practical aspects of data analysis in this course

We are also the creators of some of the most popular online courses – with over 300,000 enrollments and thousands of 5-star reviews like these ones:

This is very good, i love the fact the all explanation given can be understood by a layman – Joshua

Thank you Author for this wonderful course. You are the best and this course is worth any price. – Daisy

Our Promise

Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message.

Download Practice files, take Practice test, and complete Assignments

With each lecture, there are class notes attached for you to follow along. You can also take practice test to check your understanding of concepts. There is a final practical assignment for you to practically implement your learning.

What is covered in this course?

This course teaches you all the steps of creating a Neural network based model i.e. a Deep Learning model, to solve business problems.

Below are the course contents of this course on ANN:

Part 1 (Section 2)- Python basics

This part gets you started with Python.

This part will help you set up the python and Jupyter environment on your system and it’ll teach you how to perform some basic operations in Python. We will understand the importance of different libraries such as Numpy, Pandas & Seaborn.

Part 2 (Section 3-6) – ANN Theoretical Concepts

Who this course is for:
People pursuing a career in data science
Working Professionals beginning their Deep Learning journey
Anyone curious to master image recognition from Beginner level in short span of time

Enroll Now

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