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Deep Learning 2022 🚀

NLP Computer Vision Transformers PyTorch Machine Learning Deep Learning GANs Object Detection Object Segmentation Image Classification CNN RNN Crypto Prediction

Welcome to Deep Learning 2022! This repository serves as a central hub for various deep learning projects created throughout the year. Explore the table below to dive into each project and discover the innovations and techniques used in deep learning research and applications.

Project Description Link
McCulloch-Pitts Model Implementation of the foundational McCulloch-Pitts neuron model. GitHub
Adaline/Madaline Network Study and implementation of Adaline and Madaline neural networks. GitHub
MLP Regression Multi-Layer Perceptron model for regression tasks. GitHub
AutoEncoders for Classification Using AutoEncoders in classification tasks. GitHub
Shallow CNN for Image Classification Implementation of a shallow CNN for image classification. GitHub
Automated Diagnosis of Pneumonia Pneumonia diagnosis using EfficientNet on chest X-ray images. GitHub
Eurosat Deep Learning Deep learning applied to the Eurosat dataset for satellite image classification. GitHub
Vision Transformers Implementing Vision Transformers for image analysis. GitHub
Object Detection and Counting Techniques for object detection and counting in images. GitHub
YOLOv8 Track Coordinates Center Tracking object coordinates with YOLOv8. GitHub
Estimating Cryptocurrency Prices Predict the prices of cryptocurrencies using LSTM and GRU models. GitHub
Image Captioning Automatic captioning of images using deep learning. GitHub
Intent Classification Classifying user intent in natural language processing. GitHub
Extractive Question Answering Building a model for extractive question answering. GitHub
Variational AutoEncoder (VAE) Exploring VAEs for generative model tasks. GitHub
Conditional DCGAN Implementing Conditional Deep Convolutional GANs. GitHub

Explore these repositories to understand the depth and breadth of work done in the field of deep learning in 2022. Happy learning!

Project Overview 🚀

In this repository, we explore different aspects of deep learning through various projects:

  • McCulloch-Pitts Model 🧠: Understanding the basics of neural computation.
  • Adaline/Madaline Network 🔍: Delving into early neural network architectures for pattern recognition.
  • MLP Regression 📉: Implementing Multi-Layer Perceptron models for regression analysis.
  • AutoEncoders for Classification 🎭: Leveraging autoencoders for efficient data classification.
  • Shallow CNN for Image Classification 🖼️: Simplifying Convolutional Neural Networks for image classification tasks.
  • Automated Diagnosis of Pneumonia 🏥: Utilizing deep learning for medical imaging and pneumonia diagnosis.
  • Eurosat Deep Learning 🛰️: Applying deep learning techniques to satellite image classification.
  • Vision Transformers 👁️: Exploring the capabilities of Vision Transformers in image analysis.
  • Object Detection and Counting 📦: Innovative methods for detecting and counting objects in images.
  • YOLOv8 Track Coordinates Center 📍: Advanced object tracking with the latest YOLO technology.
  • Image Captioning 📝: Creating descriptive captions for images through deep learning models.
  • Intent Classification 💬: Enhancing natural language understanding with intent classification.
  • Extractive Question Answering ❓: Developing models for accurate question answering in texts.
  • Variational AutoEncoder (VAE) 🌀: Investigating generative modeling and representation learning with VAEs.
  • Conditional DCGAN 🌌: Experimenting with Deep Convolutional GANs for generating conditional images.

Technologies Used 💻

  • Python 🐍
  • TensorFlow 🧠
  • Keras 🌟
  • PyTorch 🔥
  • OpenCV 📸
  • Scikit-learn 🔍

Installation and Usage 🛠️

Instructions on how to install and use each project are available within the individual project directories.

Contributing 🤝

We welcome contributions to our projects! Please read the contributing guidelines in each project directory before making a pull request.

License 📄

This repository is licensed under the MIT License - see the LICENSE file for details.

Contact 📧

For any inquiries or further information, please contact.

Thank you for visiting our Deep Learning 2022 repository! 🙏