Deep_Learning

Deep learning assignments will be posted here soon.

Deep Learning Summer School Assignments

Welcome to my repository for the assignments completed during my deep learning summer school. This collection showcases a series of projects covering foundational to advanced topics in machine learning and deep learning, structured according to the weekly curriculum.

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📚 Assignments & Topics Covered

This repository is organized by week, reflecting the structure of my summer school program. Each assignment will be uploaded as a Google Colab notebook (.ipynb file).

Week	Topic / Assignment	Status
🧠 1	Laying the Foundation
	TensorFlow & PyTorch Basics	(To be uploaded soon)
🏗️ 2	Building Core Architectures
	CNNs for Image Classification	(To be uploaded soon)
	Transfer Learning with Pre-trained CNNs	(To be uploaded soon)
	Recurrent Neural Networks (RNNs)	(To be uploaded soon)
	Implementing Transformers (Hugging Face)	(To be uploaded soon)
🚀 3	Exploring the Cutting-Edge
	Generative AI: Autoencoders	(To be uploaded soon)
	Generative AI: GANs	(To be uploaded soon)
	Generative AI: Diffusion Models	(To be uploaded soon)
	Explainable AI (XAI)	(To be uploaded soon)
🌍 4	From Code to Capstone
	Applications & Capstone Project	(To be uploaded soon)

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🛠️ Technologies & Libraries Used

The solutions are implemented using Python 3 and rely on the following core libraries:

• Numerical & Data Handling:
  • NumPy
  • Pandas
• Deep Learning Frameworks:
  • PyTorch
  • TensorFlow (with the Keras backend)
• NLP & Transformer Libraries:
  • Hugging Face Transformers
  • Hugging Face Diffusers
• Machine Learning & Visualization:
  • Scikit-learn
  • Matplotlib
  • Seaborn
• Explainable AI:
  • LIME

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⚡ How to Run

The assignments are in the form of Jupyter/Google Colab notebooks (.ipynb files).

1. Clone the repository:

   git clone https://github.com/AwkJay/Deep_Learning.git

2. Open in Google Colab: Once the notebooks are uploaded, the easiest way to run them will be to open them directly in Google Colab.
3. Dependencies: Any special libraries required for a specific notebook (like diffusers or lime) are typically installed at the beginning of the notebook file with a !pip install ... command.

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Thank you for visiting my repository!