IIRF Online > Development > Data Science > Deep Learning > Deep Learning A-Z 2024: Neural Networks, AI & ChatGPT Prize
Deep Learning A-Z 2024: Neural Networks, AI & ChatGPT Prize by Udemy
Learn to create Deep Learning models in Python from two Machine Learning, Data Science experts. Code templates included.
Course Highlights
- Understand the intuition behind Artificial Neural Networks
- Apply Artificial Neural Networks in practice
- Understand the intuition behind Convolutional Neural Networks
- Apply Convolutional Neural Networks in practice
- Understand the intuition behind Recurrent Neural Networks
- Apply Recurrent Neural Networks in practice
- Understand the intuition behind Self-Organizing Maps
- Apply Self-Organizing Maps in practice
- Understand the intuition behind Boltzmann Machines
- Apply Boltzmann Machines in practice
- Understand the intuition behind AutoEncoders
- Apply AutoEncoders in practice
Skills you will learn!
Curriculum
4 Topics
Welcome Challenge!
What is Deep Learning?
Get the Datasets here
EXTRA: Use ChatGPT to Boost your Deep Learning Skills
1 Topic
Welcome to Part 1 - Artificial Neural Networks
9 Topics
What You'll Need for ANN
Plan of Attack
The Neuron
The Activation Function
How do Neural Networks work?
How do Neural Networks learn?
Gradient Descent
Stochastic Gradient Descent
Backpropagation
8 Topics
Business Problem Description
IMPORTANT NOTE
Building an ANN - Step 1
Check out our free course on ANN for Regression
Building an ANN - Step 2
Building an ANN - Step 3
Building an ANN - Step 4
Building an ANN - Step 5
1 Topic
Welcome to Part 2 - Convolutional Neural Networks
10 Topics
What You'll Need for CNN
Plan of attack
What are convolutional neural networks?
Step 1 - Convolution Operation
Step 1(b) - ReLU Layer
Step 2 - Pooling
Step 3 - Flattening
Step 4 - Full Connection
Summary
Softmax & Cross-Entropy
8 Topics
IMPORTANT NOTE
Building a CNN - Step 1
Building a CNN - Step 2
Building a CNN - Step 3
Building a CNN - Step 4
Building a CNN - Step 5
Quick Note
Building a CNN - FINAL DEMO!
1 Topic
Welcome to Part 3 - Recurrent Neural Networks
7 Topics
What You'll Need for RNN
Plan of attack
The idea behind Recurrent Neural Networks
The Vanishing Gradient Problem
LSTMs
Practical intuition
EXTRA: LSTM Variations
16 Topics
IMPORTANT NOTE
Building a RNN - Step 1
Building a RNN - Step 2
Building a RNN - Step 3
Building a RNN - Step 4
Building a RNN - Step 5
Building a RNN - Step 6
Building a RNN - Step 7
Building a RNN - Step 8
Building a RNN - Step 9
Building a RNN - Step 10
Building a RNN - Step 11
Building a RNN - Step 12
Building a RNN - Step 13
Building a RNN - Step 14
Building a RNN - Step 15
2 Topics
Evaluating the RNN
Improving the RNN
1 Topic
Welcome to Part 4 - Self Organizing Maps
10 Topics
Plan of attack
How do Self-Organizing Maps Work?
Why revisit K-Means?
K-Means Clustering (Refresher)
How do Self-Organizing Maps Learn? (Part 1)
How do Self-Organizing Maps Learn? (Part 2)
Live SOM example
Reading an Advanced SOM
EXTRA: K-means Clustering (part 2)
EXTRA: K-means Clustering (part 3)
5 Topics
How to get the dataset
Building a SOM - Step 1
Building a SOM - Step 2
Building a SOM - Step 3
Building a SOM - Step 4
4 Topics
Mega Case Study - Step 1
Mega Case Study - Step 2
Mega Case Study - Step 3
Mega Case Study - Step 4
1 Topic
Welcome to Part 5 - Boltzmann Machines
8 Topics
Plan of attack
Boltzmann Machine
Energy-Based Models (EBM)
Editing Wikipedia - Our Contribution to the World
Restricted Boltzmann Machine
Contrastive Divergence
Deep Belief Networks
Deep Boltzmann Machines
19 Topics
How to get the dataset
Installing PyTorch
Building a Boltzmann Machine - Introduction
Same Data Preprocessing in Parts 5 and 6
Building a Boltzmann Machine - Step 1
Building a Boltzmann Machine - Step 2
Building a Boltzmann Machine - Step 3
Building a Boltzmann Machine - Step 4
Building a Boltzmann Machine - Step 5
Building a Boltzmann Machine - Step 6
Building a Boltzmann Machine - Step 7
Building a Boltzmann Machine - Step 8
Building a Boltzmann Machine - Step 9
Building a Boltzmann Machine - Step 10
Building a Boltzmann Machine - Step 11
Building a Boltzmann Machine - Step 12
Building a Boltzmann Machine - Step 13
Building a Boltzmann Machine - Step 14
Evaluating the Boltzmann Machine
1 Topic
Welcome to Part 6 - AutoEncoders
10 Topics
Plan of attack
Auto Encoders
A Note on Biases
Training an Auto Encoder
Overcomplete hidden layers
Sparse Autoencoders
Denoising Autoencoders
Contractive Autoencoders
Stacked Autoencoders
Deep Autoencoders
16 Topics
How to get the dataset
Installing PyTorch
Same Data Preprocessing in Parts 5 and 6
Building an AutoEncoder - Step 1
Building an AutoEncoder - Step 2
Building an AutoEncoder - Step 3
Homework Challenge - Coding Exercise
Building an AutoEncoder - Step 4
Building an AutoEncoder - Step 5
Building an AutoEncoder - Step 6
Building an AutoEncoder - Step 7
Building an AutoEncoder - Step 8
Building an AutoEncoder - Step 9
Building an AutoEncoder - Step 10
Building an AutoEncoder - Step 11
THANK YOU Video
1 Topic
Annex - Get the Machine Learning Basics
5 Topics
What You Need for Regression & Classification
Simple Linear Regression Intuition - Step 1
Simple Linear Regression Intuition - Step 2
Multiple Linear Regression Intuition
Logistic Regression Intuition
4 Topics
Data Preprocessing
The Machine Learning process
Splitting the data into a Training and Test set
Feature Scaling
19 Topics
Getting Started - Step 1
Getting Started - Step 2
Importing the Libraries
Importing the Dataset - Step 1
Importing the Dataset - Step 2
Importing the Dataset - Step 3
For Python learners summary of Object-oriented programming: classes & objects
Taking care of Missing Data - Step 1
Taking care of Missing Data - Step 2
Encoding Categorical Data - Step 1
Encoding Categorical Data - Step 2
Encoding Categorical Data - Step 3
Splitting the dataset into the Training set and Test set - Step 1
Splitting the dataset into the Training set and Test set - Step 2
Splitting the dataset into the Training set and Test set - Step 3
Feature Scaling - Step 1
Feature Scaling - Step 2
Feature Scaling - Step 3
Feature Scaling - Step 4
19 Topics
Logistic Regression Intuition
Maximum Likelihood
Logistic Regression in Python - Step 1a
Logistic Regression in Python - Step 1b
Logistic Regression in Python - Step 2a
Logistic Regression in Python - Step 2b
Logistic Regression in Python - Step 3a
Logistic Regression in Python - Step 3b
Logistic Regression in Python - Step 4a
Logistic Regression in Python - Step 4b
Logistic Regression in Python - Step 5
Logistic Regression in Python - Step 6a
Logistic Regression in Python - Step 6b
Logistic Regression in Python - Step 7a
Logistic Regression in Python - Step 7b
Logistic Regression in Python - Step 7c
Logistic Regression in Python - Step 7 (Colour-blind friendly image)
Machine Learning Regression and Classification EXTRA
EXTRA CONTENT: Logistic Regression Practical Case Study
2 Topics
Huge Congrats for completing the challenge!
BONUS: Cloud Skills for ML & AI (COUPON inside)
Deep Learning A-Z 2024: Neural Networks, AI & ChatGPT Prize
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