Deep Learning with Python: Hands-On Introduction to Deep Learning Models
1h 55mIntermediate2025-02-27
Authors
Frederick Nwanganga
Information Technology Professional and Teacher
Course details
Get up and running with deep learning using Python. In this beginner-friendly course, instructor Frederick Nwanganga covers the fundamental concepts and techniques necessary to understand and implement basic deep learning models. Discover practical applications with hands-on coding exercises designed to prepare you for more advanced deep learning topics.
Learning objectives
Understand the fundamental concepts of neural networks and deep learning.
Explain the essential mathematical concepts that underpin deep learning.
Build a deep learning model in Python and evaluate its performance.
Learning objectives
Understand the fundamental concepts of neural networks and deep learning.
Explain the essential mathematical concepts that underpin deep learning.
Build a deep learning model in Python and evaluate its performance.
Skills covered
Neural Networks and Deep LearningPythonArtificial Intelligence (AI)Programming LanguagesOpen SourceSoftware DevelopmentOne-Off
Concepts
0. Introduction
- 01 - Getting started with deep learning
- 02 - What you should know
- 03 - Using the exercise files
1. Fundamentals of Neural Networks
- 04 - What are artificial neural networks
- 05 - How do neural networks make predictions
- 06 - Activation functions in neural networks
- 07 - How does a neural network learn
2. Introduction to Deep Learning
- 08 - What is deep learning
- 09 - Types of deep learning models
- 10 - The evolution of AI, machine learning, and deep learning
- 11 - Real-world applications of deep learning
- 12 - Challenges with deep learning
3. Mathematical Foundations of Deep Learning
- 13 - Vectors and matrices
- 14 - Tensors
- 15 - Derivatives, partial derivatives, and the chain rule
- 16 - Gradient descent
4. Text Classification with Deep Neural Networks
- 17 - Preparing to build a deep learning model in Python
- 18 - Defining a deep learning model in Python
- 19 - Training a deep learning model in Python
5. Model Performance Metrics
- 20 - Evaluating a deep learning model - Predictive accuracy
- 21 - Evaluating a deep learning model - Confusion matrix
- 22 - Evaluating a deep learning model - Precision
- 23 - Evaluating a deep learning model - Recall
- 24 - Evaluating a deep learning model - F1 score
Conclusion
- 25 - Continuing on with deep learning