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Cancer Detection Using Deep Learning | Deep Learning Projects | Deep Learning Training | Edureka



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๐Ÿ”ฅEdureka Deep Learning With TensorFlow (๐”๐ฌ๐ž ๐‚๐จ๐๐ž: ๐˜๐Ž๐”๐“๐”๐๐„๐Ÿ๐ŸŽ): https://www.edureka.co/ai-deep-learning-with-tensorflow
This Edureka video on ๐‚๐š๐ง๐œ๐ž๐ซ ๐ƒ๐ž๐ญ๐ž๐œ๐ญ๐ข๐จ๐ง ๐”๐ฌ๐ข๐ง๐  ๐ƒ๐ž๐ž๐ฉ ๐‹๐ž๐š๐ซ๐ง๐ข๐ง๐ , will help you understand how to develop models using Convolution Neural Networks. We will also have a discussion on improving model accuracy using pretrained models. Below are the topics covered in Cancer Detection Using Deep Learning video :
00:00:00 Introduction
00:00:52 Introduction to Deep Learning
00:02:57 Deep Learning General Intuition
00:05:43 Image Processing Using DL
00:16:54 Brain Tumor Detection Using Custom Model
01:07:43 Transfer Learning
01:11:21 CNN Architectures

๐Ÿ”นCheck our complete Deep Learning With TensorFlow playlist here: https://goo.gl/cck4hE
๐Ÿ”นCheck our complete Deep Learning With TensorFlow Blog Series: http://bit.ly/2sqmP4s
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#edureka #edurekadeeplearning #deeplearningwithtensorflow #cancerdetectionusingdeeplearning #convolutionneuralnetworks #deeplearningpretrainedmodels #deepearningtutorial #edurekatraining

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๐Ÿ”…๐Ÿ”…How it Works?

1. This is a 5 Week Instructor led Online Course.
2. Course consists of 30 hours of online classes, 20 hours of assignment, 20 hours of project
3. We have a 24×7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
4. You will get Lifetime Access to the recordings in the LMS.
5. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate!

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๐Ÿ”…๐Ÿ”…About the Course

Why Learn Deep Learning With TensorFlow?
TensorFlow is one of the best libraries to implement Deep Learning. TensorFlow is a software library for numerical computation of mathematical expressions, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning.

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