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autoencoders

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Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

  • Updated Apr 23, 2020
  • Jupyter Notebook

a novel architecture that leverages Autoencoders to superimpose the hidden representations of a base model and a fine-tuned model within a shared parameter space. Using B-spline-based blending coefficients and autoencoders that adaptively reconstruct the original hidden states based on the input data distribution.

  • Updated Aug 1, 2025
  • Jupyter Notebook

This repository explores the variety of techniques and algorithms commonly used in deep learning and the implementation in MATLAB and PYTHON

  • Updated Dec 9, 2022
  • Jupyter Notebook

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