Deep Learning A-Z 2025: Neural Networks, AI & ChatGPT Prize
$0.99
Instructor:
Kirill Eremenko, Hadelin of Ponteves, SuperDataScience Team, Ligency TeamCategory:
Artificial intelligence is growing exponentially. There is no doubt about that. Self-driving cars are clocking up millions of miles, IBM Watson is diagnosing patients better than armies of doctors and Google Deepmind’s AlphaGo beat the World champion at Go – a game where intuition plays a key role.
But the further AI advances, the more complex become the problems it needs to solve. And only Deep Learning can solve such complex problems and that’s why it’s at the heart of Artificial intelligence.
What you’ll learn
- 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
Course content
2727 sections • 189 lectures • Total duration 22 h 32 min
Welcome to the course!
Part 1 - Artificial Neural Networks
ANN Intuition
Building an ANN
Part 2 - Convolutional Neural Networks
CNN Intuition
Building a CNN
Part 3 - Recurrent Neural Networks
RNN Intuition
Building a RNN
Evaluating and Improving the RNN
Part 4 - Self Organizing Maps
SOMs Intuition
Building and SOM
Mega Case Study
Part 5 - Boltzmann Machines
Boltzmann Machine Intuition
Building a Boltzmann Machine
Part 6 - AutoEncoders
AutoEncoders Intuition
Building an AutoEncoder
Annex - Get the Machine Learning Basics
Regression & Classification Intuition
Data Preprocessing
Data Preprocessing in Python
Logistic Regression
Congratulations!! Don't forget your Prize :)