Convolutional Neural Networks with Pytorch

Category: Tutorial


Posted on 2021-07-15, by elegance.

Description



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MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 22 lectures (4h 45m) | Size: 4.1 GB




Learn how to implement a Convolutional Neural Netwk using Pytch
What you'll learn:
Learn what is a Convolutional Neural Netwk
Learn what is Deep Learning
Learn what is a Neural Netwk
Learn what is convolution
Learn parameters required in convolution
Learn different layers in a convolutional neural netwk
Learn the mathematics behind the neural netwks
Learn how to train a neural netwk
Learn how to use Pytch framewk to build a Convolutional Neural Netwk model
Learn how to use Python to build a Deep Learning project
Learn how to use Jupyter notebook to build a Deep Learning project
Learn how to create and train a neural netwk model with Pytch
Learn how to analyze a neural netwk training and measure the perfmance while training
Learn how to evaluate a neural netwk model and get metrics to analyze general perfmance
Learn how to apply changes and explation analysis in der to improve the neural netwk model

Requirements
Basic Python knowledge is required
No previous knowledge in Convolutional Neural Netwks is required
No previous knowledge in Deep Learning is required
No previous knowledge in Machine Learning is required
No previous knowledge in Pytch is required

Description
In this course, you are going to learn what is and how to implement a Convolutional Neural Netwk model. To do this, you will use the library Pytch using Python programming Language, a tool that allows you to easily build a neural netwk model.

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

After the theetical part, you will build a practical project in which you will build a convolutional neural netwk model to classify images into different classes (like classify a picture of a dog as a dog). To do this you will use Pytch, a library that allows you to create and train a neural netwk 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 theetical 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 exple different options in der to improve the model perfmance.

You don't need previous knowledge on Deep Learning, Convolutional Neural Netwks Pytch, because you will learn the basics you need in der 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 f
Anyone who wants to learn about how to implement a convolutional neural netwk using Python and Pytch
Anyone who wants to learn about how a Deep Learning project is developed

I recommends Buy premimum account f High speed+parallel downloads!

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