PyTorch for Deep Learning Bootcamp: Zero to Mastery
Learn How to Use PyTorch (Facebook Library) for Deep Learning with Practical Examples
Created by Navid Shirzadi | 9 hours on-demand video course
Deep learning has become one of the most popular machine learning techniques in recent years, and PyTorch has emerged as a powerful and flexible tool for building deep learning models. In this PyTorch for Deep Learning Bootcamp course, you will learn the fundamentals of deep learning and how to implement neural networks using PyTorch.
Through a combination of lectures, hands-on coding sessions, and projects, you will gain a deep understanding of the theory behind deep learning techniques such as deep Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs). You will also learn how to train and evaluate these models using PyTorch, and how to optimize them using techniques such as stochastic gradient descent and backpropagation. During the PyTorch for Deep Learning Bootcamp: Zero to Mastery course, I will also show you how you can use GPU instead of CPU and increase the performance of the deep learning calculation.
What you’ll learn
- Understand the basic concepts about neural network and how it works
- Use PyTorch for Linear Regression using Multilayer Perceptron (MLP)
- Use PyTorch for image classification using Deep Artificial Neural Network (ANN)
- Learn how to work with different data types such as tensors and arrays
- Use PyTorch for image classification using Convolutional Neural Network (CNN)
- Use PyTorch for time series prediction using Recurrent Neural Network (RNN)
- Use PyTorch for Natural Language Processing (NLP)
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