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backpropagation_regression.py
mnist_classification.py

--- Hi, I'm Ahmed Ali! Founder of Data X, where we aim to help you and your business with data science, data analysis, machine learning, and AI solutions. Please don’t forget to follow me for more projects like this. --- # 100 Days of Deep Learning Repository Welcome to the 100 Days of Deep Learning repository! This extensive collection is dedicated to showcasing a diverse array of deep learning projects, each designed to explore various concepts and techniques in depth. Over 100 days, you'll find hands-on implementations and practical examples covering every major topic in deep learning. Dive into projects that span a wide range of deep learning subfields, including: 1. **Neural Networks**: Basics of Neural Networks, Activation Functions, Backpropagation 2. **Convolutional Neural Networks (CNNs)**: Image Classification, Object Detection, Image Segmentation 3. **Recurrent Neural Networks (RNNs)**: Sequence Prediction, Text Generation, Time Series Forecasting 4. **Long Short-Term Memory Networks (LSTMs)**: Sentiment Analysis, Language Modeling, Anomaly Detection 5. **Generative Adversarial Networks (GANs)**: Image Generation, Style Transfer, Data Augmentation 6. **Autoencoders**: Dimensionality Reduction, Anomaly Detection, Data Compression 7. **Transfer Learning**: Fine-Tuning Pretrained Models, Feature Extraction, Domain Adaptation 8. **Deep Reinforcement Learning**: Q-Learning, Policy Gradients, Deep Q-Networks (DQN) 9. **Natural Language Processing (NLP)**: Named Entity Recognition, Machine Translation, Text Summarization 10. **Object Detection**: YOLO, SSD, Faster R-CNN 11. **Image Segmentation**: U-Net, Mask R-CNN, Fully Convolutional Networks (FCNs) 12. **Time Series Analysis**: LSTM Networks for Forecasting, Attention Mechanisms 13. **Neural Architecture Search**: Automated Model Design, Hyperparameter Tuning 14. **Advanced Optimization**: Adam, RMSprop, Learning Rate Schedulers 15. **Deep Learning Frameworks**: TensorFlow, Keras, PyTorch Each project is crafted to provide practical insights and hands-on experience with deep learning techniques, tools, and frameworks. This repository serves as a comprehensive resource for anyone looking to master deep learning and apply it to real-world problems. # CLICK TO VIEW SOCIALS | Platform | Icon | |--------------------------------------------|--------------------------------------------------------------------------------------| | [LinkedIn](https://www.linkedin.com/in/rajaahmedalikhan) |  | | [My website](https://dataxofficial.com) |  | | [Contributions on Kaggle](https://www.kaggle.com/datascientist97) |  | | [Subscribe on YouTube](https://www.youtube.com/@datax_official) |  | | [Email at: Data X](mailto:datascientist097@gmail.com) |  | ---

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