Create and Visualize Your First Perceptron and Feed Forward Network in Python

Learn to create and visualize your first Perceptron (P) and Feed Forward (FF) Network in Python with this beginner-friendly tutorial. Designed for those new to neural networks, explore the fundamentals of deep learning without requiring prior knowledge of math, statistics, or machine learning. Utilize Keras and TensorFlow to build neural networks from scratch, defining inputs, outputs, and intermediate layers. Combine network visualization techniques with hands-on coding to gain a clear understanding of deep learning concepts. Progress from creating a simple Perceptron to developing a Feed Forward Network, and even experiment with a small Convolutional Neural Network (CNN). By the end of this 44-minute video, you'll have practical experience in implementing various neural network architectures and using pre-trained CNNs, setting a solid foundation for your journey into deep learning.

- Tutorial Starts
- Content Intro
- Today's content
- Previous Tutorials
- Getting Started
- 3 ways for neural network
- Creating Perceptron
- Creating Feed Forward Network
- Creating Smallest CNN
- Using Pre-trained CNN
- Tutorial Source Code
- Recap