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


## Calculate the perceptron output

Given the two data points: $x_1$ and $x_2$ with values 2 and 3 respectively, compute the predicted value with the given weights of $w_1=2$ and $w_2=3$ and bias $b=0.1$.


# Calculate the perceptron output

Given the two data points: $x_1$ and $x_2$ with values 2 and 3 respectively, compute the predicted value with the given weights of $w_1=2$ and $w_2=3$ and bias $b=0.1$.

Learn how to code the single-layer feedforward operation.

✨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

Coding the Perceptron Forward Propagation

Calculate the perceptron output