This is a comprehensive module for learners who wish to learn deep learning techniques with practical examples.

Neural Networks: Beginners to Advanced

This beginner level and highly comprehensive module is intended for learners who are familiar with Python programming. You will become familiar with the fundamental concepts and terminologies that are used in deep learning. In addition, this module will help you understand the importance of deep learning techniques. You will examine simple models like perceptron before learning more complex yet powerful deep learning models. The module will provide hands-on practical knowledge of how to code simple and complex deep learning models in NumPy, a powerful Python library, and Keras, a cutting-edge library for deep learning in Python. By the end of the module, you should have a general understanding of the basics of deep learning, and you will be equipped with the right tools to learn more advanced concepts.

Deep Learning with Keras

## What is machine learning?

Arthur Samuel defines Machine learning as:

> "_Machine Learning is a field of study that gives computers the ability to learn without being explicitly programmed_." **~ Arthur Samuel**


## Traditional programming vs. machine learning

In traditional programming, the algorithm is known and a function is written to produce the output. In Machine learning, you know the input and the output but the algorithm is the unknown that produces the output.






|**Traditional Programming**|**Machine Learning**|  
|---|---|
|  Input data | Take input and output  |  
|  Apply logic to it to produce a result |Figure out the algorithm   | 

# What is machine learning?

Arthur Samuel defines Machine learning as:

> "_Machine Learning is a field of study that gives computers the ability to learn without being explicitly programmed_." **~ Arthur Samuel**


# Traditional programming vs. machine learning

In traditional programming, the algorithm is known and a function is written to produce the output. In Machine learning, you know the input and the output but the algorithm is the unknown that produces the output.






Learn the fundamental concepts of Machine learning.

✨Introduction to Deep Learning

✨Simple Perceptron Models in NumPY

✨Towards Deep Neural Networks in NumPY

🖥️ Project: Build a Letter Classification Model

Deep Learning in NumPy Exam

✨Building Deep Learning Models with Keras

✨Fine-tune Keras Model

🖥️ Project: Build a Digit Recognition Model

✨Conclusion

Fundamentals of Machine Learning

What is machine learning?

Traditional programming vs. machine learning

Traditional Programming	Machine Learning
Input data	Take input and output
Apply logic to it to produce a result	Figure out the