Deeplearning: Convolutional Neural Network for Developers
This course will teach you Deep learning focusing on Convolution Neural Networks architectures
Deep Learning,Development,Data Science
Lectures -11
Duration -2.5 hours
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Course Description
This course will teach you Deep learning focusing on Convolution Neural Net architectures. It is structured to help you genuinely learn Deep Learning by starting from the basics until advanced concepts. We will begin learning what it is under the hood of Deep learning frameworks like Tensorflow and Pytorch, then move to advanced Deep learning Architecture with Pytorch.
During our journey, we will also have projects exploring some critical concepts of Deep learning and computer vision, such as: what is an image; what are convolutions; how to implement a vanilla neural network; how back-propagation works; how to use transfer learning and more.
All examples are written in Python and Jupyter notebooks with tons of comments to help you to follow the implementation. Even if you don’t know Python well, you will be able to follow the code and learn from the examples.
The advanced part of this project will require GPU but don’t worry because those examples are ready to run on Google Colab with just one click, no setup is required, and it is free! You will only need to have a Google account.
By following this course until the end, you will get insights, and you will feel empowered to leverage all recent innovations in the Deep Learning field to improve the experience of your projects.
Goals
- Convolutional neural network architectures
- Computer vision algorithims
- How to implement a Deep Neural Network from scratch
- How the back-propagation algorithm works
- How to search similar images
- How to build multi task models
Prerequisites
- No Deep Learning experience is needed. You will learn everything you need to know
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Curriculum
Check out the detailed breakdown of what’s inside the course
Course lessons
11 Lectures
-
Introduction 05:27 05:27
-
Working with Images and Numpy 06:09 06:09
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Image convolution with Numpy 06:55 06:55
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Building a Artificial Neural network from scratch 11:51 11:51
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Building a neural network from scratch - part 2 18:09 18:09
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Building a neural network with PyTorch 08:53 08:53
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Convolution Neural Network with PyTorch 26:50 26:50
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CNN and Autoencoder - image interpolation 19:01 19:01
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Image similarity - Image reverse search engine 09:39 09:39
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Multitasking model 34:34 34:34
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Playing with Generative Adversarial Networks(GAN) 22:14 22:14
Instructor Details
![Alexsandro Souza](https://www.tutorialspoint.com/assets/profiles/532139/profile/200_2355823-1665172179.jpg)
Alexsandro Souza
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