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dynamic-learning-rate

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dmickelson / Rock-paper-scissors

This Rock Paper Scissors AI project combines machine learning and data science techniques to create a highly effective player. It uses an LSTM neural network for move prediction, online learning for real-time adaptation, and pattern recognition. The AI employs opponent modeling, ensemble decision-making, and dynamic learning rates .

python tensorflow keras lstm adaptive-learning feature-engineering lstm-neural-networks opponent-modeling dynamic-learning-rate

Updated Sep 3, 2024
Python

Kaitannn / Polling-Optimisation-for-Gradient-Descent

Expediting Convergence via Polling Optimisation for Gradient Descent in Neural Networks

optimiser bootstrap-aggregating learning-rate-hyperparameter ensemble-hybrid-models adaptive-learning-approach dynamic-learning-rate

Updated Mar 17, 2024
Batchfile

OmidGhadami95 / metaphor-detection-cnn-lstm

Metaphor detection using cnn lstm

nlp natural-language-processing cnn lstm tokenization imbalanced-data lemmatization bidirectional-lstm metaphor lstm-cnn metaphor-detection dynamic-learning-rate

Updated Dec 28, 2024
Jupyter Notebook

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