This repository provides practical applications and resources for the Udemy course "Introduction to Deep Learning." It is designed for individuals looking to enter the field of artificial intelligence and develop "learning" applications, offering a comprehensive guide from foundational concepts to advanced techniques.

How It Works

The project utilizes Python with TensorFlow and Keras to implement various deep learning models. It covers core architectures like Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Long Short-Term Memory (LSTM), alongside advanced topics such as Capsule Networks, Generative Adversarial Networks (GAN), and Reinforcement Learning (RL). The approach emphasizes practical application through hands-on examples.

Quick Start & Requirements

• Primary Install/Run: Google Colab is recommended for running the provided .ipynb files directly via links. Local execution is also supported by downloading files.
• Prerequisites: Python, TensorFlow, Keras, NumPy. Google Colab provides GPU access.
• Resources: Links to Google Colab notebooks for each section are provided.

Highlighted Details

• Covers a broad spectrum of deep learning models: ANN, CNN, RNN, LSTM, CapsNet, GAN, RL.
• Includes practical implementations for tasks like image recognition (MNIST, Fashion MNIST, VGG-16, ResNet-50), object detection (YOLO), sentiment analysis, and generative data creation.
• Offers guidance on common machine learning problems, optimization techniques, regularization, transfer learning, and fine-tuning.
• Provides links to supplementary resources for getting started with AI/Deep Learning and using Google Colab with GPU/TPU.

Maintenance & Community

The repository is maintained by Merve Ayyüce Kızrak. The README expresses gratitude to contributors and supporters.

Licensing & Compatibility

The repository does not explicitly state a license. Compatibility for commercial use or closed-source linking is not specified.

Limitations & Caveats

The repository is primarily a collection of code examples and resources tied to a specific Udemy course. While it offers a broad overview, in-depth explanations and troubleshooting for local setup are directed to the course content.