Welcome to our tutorials on Deep Learning with Python! Whether you are a beginner or looking to expand your knowledge, these guides will help you understand the fundamentals and advanced concepts of deep learning.
Getting Started
Before diving into deep learning, it's essential to have a solid understanding of Python programming. If you're new to Python, we recommend starting with our Python Basics Tutorial.
Tutorials
1. Introduction to Neural Networks
A neural network is a series of algorithms that attempt to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates. Learn more about Introduction to Neural Networks.
2. Building Your First Neural Network
In this tutorial, we'll guide you through building your first neural network using Python. We'll cover the basics of creating a neural network, training it, and making predictions. Check out Building Your First Neural Network.
3. Convolutional Neural Networks (CNNs)
Convolutional Neural Networks are a class of deep neural networks, most commonly applied to analyzing visual imagery. Learn how to build and train a CNN in Convolutional Neural Networks.
4. Recurrent Neural Networks (RNNs)
Recurrent Neural Networks are a type of artificial neural network designed to recognize patterns in sequences of data, such as time series or natural language. Discover how to implement RNNs in Recurrent Neural Networks.
Resources
To further your learning, here are some resources you might find helpful: