Deep Learning for Beginner 🎯🧠

Welcome to the Deep Learning for Beginner repository!
This project is designed to help newcomers understand the foundational concepts and practical implementations of deep learning using Python, TensorFlow, and Keras.

🚀 Whether you're starting your journey into AI or brushing up on core concepts, this repo gives you a clear, beginner-friendly introduction to deep learning.

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📚 What You'll Learn

• Understanding neural networks & deep learning fundamentals
• Using TensorFlow & Keras for building models
• Working with real-world datasets (like MNIST, Fashion MNIST)
• Data preprocessing & normalization
• Model training, evaluation & tuning
• Visualizing metrics (accuracy, loss)

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🧰 Tools & Libraries

• Python 3.x
• TensorFlow & Keras
• NumPy
• Pandas
• Matplotlib / Seaborn
• Jupyter Notebook

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📁 Project Structure

📦 Deep-Learning-for-Beginner

├── beginner_ann.ipynb # Simple Artificial Neural Network example

├── cnn_mnist.ipynb # CNN applied on MNIST dataset

├── fashion_mnist_ann.ipynb # ANN on Fashion MNIST dataset

├── README.md # Project documentation

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🚦 How to Run

1. Clone the repository:

   git clone https://github.com/udityamerit/Deep-Learning-for-Beginner.git
   cd Deep-Learning-for-Beginner
   
   

2. Install the dependencies:

   pip install -r requirements.txt

3. Launch the notebooks:

   jupyter notebook

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📊 Model Highlights

• ANN on Fashion MNIST

  • Input: 784 features (28x28 images)
  • Activation: ReLU (hidden), Softmax (output)
  • Optimizer: Adam
  • Accuracy: ~89%

• CNN on MNIST

  • Convolutional layers + MaxPooling + Dense layers
  • High accuracy with minimal overfitting

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💡 Ideal For

• Students and beginners exploring AI/ML
• Practicing deep learning workflows
• Visual learners who benefit from Jupyter Notebooks

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🔗 Useful Links

• TensorFlow Docs
• Keras Guides
• MNIST Dataset

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📬 Connect with Me

Uditya Narayan Tiwari B.Tech in CSE (AI & ML) | VIT Bhopal University 🌐 Portfolio 💼 LinkedIn 💻 GitHub

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📌 License

This project is open source and available under the MIT License.

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🌟 Show Your Support

If you like this project, don’t forget to give it a ⭐ and share it with others!