🧠 Tensor Projects Collection

A curated collection of deep learning and machine learning projects built using TensorFlow, Keras, and Python. This repository demonstrates practical implementations of computer vision, NLP, and generative AI techniques.

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📂 Repository Structure

Tensor_projects/
│
├── Brain Tumor Detection System
├── Dogs Vs Cats Image Classification
├── Email Spam Detection
├── Fashion Generator Using GANs
├── Generate Faces Using GANs
└── MNIST Digit Classification

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🚀 Projects Overview

1. 🧠 Brain Tumor Detection System

• Detects brain tumors from MRI scans using CNN

• Focuses on medical image classification

• Key concepts:

  • Convolutional Neural Networks (CNN)
  • Image preprocessing
  • Binary classification

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2. 🐶🐱 Dogs vs Cats Image Classification

• Classifies images as either dog or cat

• Classic computer vision problem

• Key concepts:

  • Data augmentation
  • Transfer learning (optional)
  • Image classification pipelines

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3. 📧 Email Spam Detection

• Classifies emails as spam or not spam

• Uses NLP techniques

• Key concepts:

  • Text preprocessing (tokenization, stemming)
  • TF-IDF / embeddings
  • Classification models

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4. 👗 Fashion Generator using GANs

• Generates synthetic fashion images

• Uses Generative Adversarial Networks

• Key concepts:

  • Generator & Discriminator architecture
  • Training GANs
  • Image synthesis

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5. 😀 Face Generator using GANs

• Generates realistic human faces

• Advanced GAN-based implementation

• Key concepts:

  • Deep Convolutional GANs (DCGAN)
  • Latent space representation
  • Image generation

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6. 🔢 MNIST Digit Classification

• Recognizes handwritten digits (0–9)

• Beginner-friendly deep learning project

• Key concepts:

  • Neural networks
  • Softmax classification
  • Benchmark dataset (MNIST)

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🛠️ Tech Stack

• Language: Python 🐍

• Libraries:

  • TensorFlow / Keras
  • NumPy
  • Pandas
  • Matplotlib / Seaborn
  • OpenCV (for image processing)

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⚙️ Installation

1. Clone the repository:

git clone https://github.com/your-username/Tensor_projects.git
cd Tensor_projects

2. Install dependencies:

pip install -r requirements.txt

(If requirements.txt is missing, install manually based on project needs.)

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▶️ How to Run

Navigate to any project folder and run:

python main.py

or open Jupyter notebooks:

jupyter notebook

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📊 Features

• Multiple real-world AI projects in one repo

• Covers:

  • Computer Vision
  • NLP
  • Generative AI

• Beginner to intermediate level implementations

• Modular and easy-to-understand structure

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🎯 Learning Outcomes

By exploring this repository, you will:

• Understand deep learning workflows
• Learn how to preprocess image and text data
• Build and train neural networks
• Work with GANs for image generation
• Gain hands-on TensorFlow experience

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🔮 Future Improvements

• Add deployment (Flask / Streamlit)
• Improve model accuracy with tuning
• Add pretrained models
• Include UI for projects
• Add dataset links and documentation

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🤝 Contributing

Contributions are welcome!

1. Fork the repo
2. Create a new branch
3. Make your changes
4. Submit a pull request

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