Pytorch For Deep Learning Bootcamp: Zero To Mastery

Learn How to Use PyTorch (Facebook Library) for Deep Learning with Practical Examples

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)

Requirements

Understanding basic Python topics (Function, for loop, etc.)

Knowing the basics of OOP is recommended

Description

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 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 course, I will also show you how you can use GPU instead of CPU and increase the performance of the deep learning calculation.In this course, I will teach you everything you need to start deep learning with PyTorch such as:NumPy Crash CoursePandas Crash CourseNeural Network Theory and IntuitionHow to Work with Torchvision datasetsConvolutional Neural Network (CNN)Long-Short Term Memory (LSTM)and much moreSince this course is designed for all levels (from beginner to advanced), we start with basic concepts and preliminary intuitions.By the end of this course, you will have a strong foundation in deep learning with PyTorch and be able to apply these techniques to various real-world problems, such as image classification, time series analysis, and even creating your own deep learning applications.

Overview

Section 1: Course Introduction & Overview

Lecture 1 Course Content

Lecture 2 Why Google Colab?

Lecture 3 Introduction to Colab Environment

Section 2: Useful Packages

Lecture 4 NumPy Basics

Lecture 5 Pandas Basics

Section 3: PyTorch Tensor Basics

Lecture 6 Introduction to Tensors

Lecture 7 Working with PyTorch Tensors

Section 4: Neural Network Basic Concepts

Lecture 8 Basic Terms About NN

Lecture 9 Activation Function

Lecture 10 How Neural Network Learn?

Lecture 11 Gradient Decent Optimization

Section 5: PyTorch for Multilayer Perceptron (MLP)

Lecture 12 PyTorch Regression Using MLP – Part1

Lecture 13 PyTorch Regression Using MLP – Part2

Lecture 14 PyTorch Regression Using MLP – Part3

Lecture 15 PyTorch Regression Using MLP – Part4

Section 6: PyTorch for Deep Artificial Neural Network (ANN)

Lecture 16 Deep Artificial Neural Network Introduction

Lecture 17 PyTorch Image Classification Using ANN – Part1

Lecture 18 PyTorch Image Classification Using ANN – Part2

Lecture 19 PyTorch Image Classification Using ANN – Part3

Lecture 20 PyTorch Image Classification Using ANN – Part4

Section 7: PyTorch for Convolutional Neural Network (CNN)

Lecture 21 Introduction

Lecture 22 Convolutional Layer (Image Filter)

Lecture 23 Pooling Layer

Lecture 24 Flattening

Lecture 25 Conclusion

Lecture 26 PyTorch Image Classification Using CNN – Part1

Lecture 27 PyTorch Image Classification Using CNN – Part2

Lecture 28 PyTorch Image Classification Using CNN – Part3

Lecture 29 PyTorch Image Classification Using CNN – Part4

Section 8: Using GPU Instead of CPU

Lecture 30 Introduction to CPU & GPU

Lecture 31 Watch if You Don't Use Colab!

Lecture 32 How to Use GPU?

Lecture 33 How to Save & Load a Model Using PyTorch

Section 9: PyTorch for Recurrent Neural Network

Lecture 34 Introduction to Recurrent Neural Network

Lecture 35 What is LSTM and How it Works?

Lecture 36 PyTorch for Time Series Forecasting Using LSTM-Part1

Lecture 37 PyTorch for Time Series Forecasting Using LSTM-Part2

Lecture 38 PyTorch for Time Series Forecasting Using LSTM-Part3

Lecture 39 PyTorch for Time Series Forecasting Using LSTM-Part4

beginner to advance python developers, data analysts, engineers and overall data science enthusiast want to learn about deep learning with PyTorch