English | MP4 | AVC 1920×1080 | AAC 44KHz 2ch | 2h 08m | 502 MB
Getting started with neural networks in PyTorch – Facebook’s great neural network framework
Artificial intelligence (AI) is the hottest topic currently out there, there’s no doubt about that. This is the future. Neural networks in particular have seen a lot of attention and they will be used everywhere -self driving cars, predictions in finance and sales forecasts – everywhere and across all industries. To be successful in the working world of tomorrow we have to expose ourselves to this interesting topic – and from the author’s personal experience – coding your own neural network is the best way to understand how they work. Besides TensorFlow there is a new very interesting deep learning framework which is developed by Facebook – PyTorch. A challenge? Indeed. But together we can do it. Excited? I hope so. See you in the first lecture. Let’s get into it.
The goal of this course is to become familiar with this framework and create your own deep neural networks – a multi-layer perceptron and a convolutional neural network for image classification.
What You Will Learn
- You will learn the PyTorch fundamentals
- You will find out how to code a deep neural network in Python
- You will come to know what learning in neural networks means
- You will be able to code a convolutional neural network in Python
- If you have taken my neural networks in TensorFlow course you can compare both frameworks (TensorFlow and PyTorch)
Table of Contents
1 Why taking this course Because…
2 How to install pytorch
3 The fundamentals
4 understanding gradient descent
5 transition to pytorch
6 linear regression in pytorch
7 A deep Neural Network in Pytorch 5
8 Convolutional Neural Networks basics
9 Convolutional Neural Networks in pytorch 1
10 Convolutional Neural Networks CNN in pytorch 2
11 Convolutional Neural Networks CNN in pytorch 3 Final Test
12 Congratulation
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