HomeCoursesIntroduction to Deep Learning & Neural Networks

Intermediate

4h 30min

Introduction to Deep Learning & Neural Networks
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Gain insights into basic and intermediate deep learning concepts, including CNNs, RNNs, GANs, and transformers. Delve into fundamental architectures to enhance your machine learning model training skills.

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Overview

This course is an accumulation of well-grounded knowledge and experience in deep learning. It provides you with the basic concepts you need in order to start working with and training various machine learning models. You will cover both basic and intermediate concepts including but not limited to: convolutional neural networks, recurrent neural networks, generative adversarial networks as well as transformers. After completing this course, you will have a comprehensive understanding of the fundamental ar...Show More

This course is an accumulation of well-grounded knowledge and experience in deep learning. It provides you with the basic concep...Show More

WHAT YOU'LL LEARN

Understanding of the most popular Deep Learning models

A solid grasp on the mathematics and the intuition behind the algorithms

A good experience with Deep Learning Programming and Pytorch

Understanding of the most popular Deep Learning models

TAKEAWAY SKILLS

Machine learning paradigms

Deep learning basics

PyTorch basics

Content

52 Lessons8 Quizzes1 Assessment11 Challenges

Learn Deep Learning

3 Lessons

Get familiar with core deep learning concepts, models, hands-on exercises, and PyTorch tools.

About this Course

Why Learn Deep Learning?

Overview of the Course

Neural Networks

6 Lessons

Walk through neural networks, including classifiers, optimization, backpropagation, and PyTorch basics.

Linear Classifiers

Optimization and Gradient Descent

Neural Networks

Backpropagation Algorithm

Build a Neural Network With Pytorch

Quiz Yourself on Neural Networks

Training Neural Networks

5 Lessons

Work your way through optimizing and training neural networks using key algorithms and techniques.

Optimization

Popular Optimization Algorithms

Activation Functions

Training in Pytorch

Quiz Yourself on Training Neural Networks

Convolutional Neural Networks

7 Lessons

Grasp the fundamentals of CNNs, including principles, applications, architectures, and improvements.

The Principles of the Convolution

Convolution in Practice

Build a Convolutional Network

Batch Normalization and Dropout

Skip Connections

CNN Architectures

Quiz Yourself on CNNs

Recurrent Neural Networks

5 Lessons

Take a closer look at RNNs, LSTMs, and custom implementation in PyTorch for sequential data.

A Simple RNN Cell

LSTM: Long Short Term Memory Cells

Writing a Custom LSTM Cell in Pytorch

Connect LSTM Cells Across Time and Space

Quiz Yourself on RNNs

Autoencoders

5 Lessons

Investigate generative learning principles and explore autoencoders for data reconstruction and generation.

Generative Learning

Basics of Autoencoders

Variational Autoencoder: Theory

Variational Autoencoder: Practice

Quiz Yourself on Autoencoders

Generative Adversarial Networks

4 Lessons

Practice using GANs to generate realistic data and evaluate with discriminators for robustness.

Generator and Discriminator

Generative Adversarial Networks in Detail

Develop a GAN with Pytorch

Quiz Yourself on GANs

Attention and Transformers

10 Lessons

Step through transformers, enhancing NLP tasks with self-attention, multi-head attention, and encoder-decoder mechanisms.

Sequence to Sequence Models

Attention

Key Concepts of Transformers

Self-Attention

Multi-Head Self-Attention

Transformers Building Blocks

The Transformer's Encoder

The Transformer's Decoder

Build a Transformer Encoder

Quiz Yourself on Transformers

Graph Neural Networks

5 Lessons

Discover the logic behind Graph Neural Networks' applications, mathematics, and implementation details.

Basics of Graphs

Mathematics for Graphs

Graph Convolutional Networks

Implementation of a GCN

Quiz Yourself on GNNs

10.

Conclusion

2 Lessons

Examine deep learning advancements, essential tools, datasets, and resources for future learning.

Where to go from here?

Appendix

Final Quiz

Assessment

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Course Author:

AI Summer

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