Comprehensive Course Description:
Convolutional Neural Networks (CNNs) are considered as game–changers in the field of computer vision, particularly after AlexNet in 2012. And the good news is CNNs are not restricted to images only. They are everywhere now, ranging from audio processing to more advanced reinforcement learning (i.e., Resnets in AlphaZero). So, the understanding of CNNs becomes almost inevitable in all the fields of Data Science. Even most of the Recurrent Neural Networks rely on CNNs these days. So, keeping all these concerns in parallel, with this course, you can take your career to the next level with an expert grip on the concepts and implementations of CNNs in Data Science.
The course ’Mastering Convolutional Neural Networks, Theory and Practice in Python‘ is crafted to reflect the in–demand skills in the marketplace that will help you in mastering the concepts and methodology with regards to Python. The course is:
Easy to understand.
Practical with live coding.
Rich with state–of–the–art and recently discovered CNN models by the champions in this field.
How is this course different?
This course has been designed for beginners. However, we will go far deep gradually.
Also, this course is a quick compilation of all the basics, and it encourages you to press forward and experience more than what you have learned. By the end of every module, you will work on the assigned Homework/tasks/activities, which will evaluate / (further build) your learning based on the previous concepts and methods. Several of these activities will be coding–based to get you up and running with implementations.
Specification: Deep Learning CNN: Convolutional Neural Networks with Python
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