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Convolutional Neural Networks with Pytorch

Convolutional Neural Networks with Pytorch
Convolutional Neural Networks with Pytorch

Convolutional Neural Networks with Pytorch

Learn how to implement a Convolutional Neural Network using Pytorch

What you’ll learn

Convolutional Neural Networks with Pytorch

  • Learn what is a Convolutional Neural Network
  • Learn what is Deep Learning
  • You learn what is a Neural Network
  • Learn what is a convolution
  • Learn parameters required in convolution
  • You learn different layers in a convolutional neural network
  • Learn the mathematics behind the neural networks
  • Learn how to train a neural network
  • Y learn how to use the Pytorch framework to build a Convolutional Neural Network model
  • Learn how to use Python to build a Deep Learning project
  • Learn how to use Jupyter notebook to build a Deep Learning project
  • You learn how to create and train a neural network model with Pytorch
  • Learn how to analyze a neural network training and measure the performance while training
  • Learn how to evaluate a neural network model and get metrics to analyze general performance
  • You learn how to apply changes and exploration analysis in order to improve the neural network mode

Requirements

  • No previous knowledge of Convolutional Neural Networks is required
  • No previous knowledge in Deep Learning is required
  • Basic Python knowledge is required
  • No previous knowledge in Machine Learning is required
  • No previous knowledge of Pytorch is required

Description

In this course, you are going to learn what is and how to implement a Convolutional Neural Network model. To do this, you will use the library Pytorch using Python programming language, a tool that allows you to easily build a neural network model.

In the first part of the course, you will learn the basic about the theory of Deep Learning and Convolutional Neural Networks and then we will go deeper in the mathematics behind these models so that you can understand how these models works, how they are trained and evaluated and with this knowledge, you can change stuff in order to improve your own models.

After the theoretical part, you will build a practical project in which you will build a convolutional neural network model to classify images into different classes (like classify a picture of a dog as a dog). To do this you will use Pytorch, a library that allows you to create and train a neural network model using Python. First, you will create the model using a specific convolutional architecture, and then you will train the model by applying all the concepts you learned in the theoretical part. After training, you will get metrics that will allow you to analyze and evaluate how good your model is. Based on the results, you will learn how to implement changes into your project so that you can learn how to explore different options in order to improve the model performance.

You don’t need previous knowledge on Deep Learning, Convolutional Neural Networks or Pytorch, because you will learn the basics you need in order to build a deep learning project using this technology.

So, get started building convolutional deep learning projects with this very practical course.

Who this course is for:

  • Anyone who wants to learn about how to implement a convolutional neural network using Python and Pytorch
  • Anyone who wants to learn about how a Deep Learning project is developed
  • Last updated 4/2021

Content From: https://www.udemy.com/course/convolutional-neural-networks-with-pytorch/
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