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kmario23 / deep-learning-drizzle

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Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

machine-learning natural-language-processing deep-neural-networks reinforcement-learning computer-vision deep-learning optimization probability deep-reinforcement-learning medical-imaging speech-recognition artificial-neural-networks pattern-recognition probabilistic-graphical-models bayesian-statistics artificial-intelligence-algorithms visual-recognition geometric-deep-learning explainable-ai graph-neural-networks
  • Updated Feb 2, 2024
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krishnakumarsekar / awesome-quantum-machine-learning

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Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web

machine-learning awesome ai qml tensorflow quantum machine-learning-algorithms artificial-intelligence quantum-computing artificial-neural-networks awesome-list fcm kmeans ant-colony-optimization quantum-programming-language hmm-model qubits knn-classification quantum-ai
  • Updated May 7, 2024
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GMvandeVen / continual-learning

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PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.

deep-learning artificial-neural-networks replay incremental-learning variational-autoencoder generative-models lifelong-learning distillation continual-learning elastic-weight-consolidation replay-through-feedback icarl gradient-episodic-memory class-incremental-learning task-incremental-learning domain-incremental-learning
  • Updated Mar 21, 2024
  • Jupyter Notebook

LiYangHart / Hyperparameter-Optimization-of-Machine-Learning-Algorithms

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Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

machine-learning deep-learning random-forest optimization svm genetic-algorithm machine-learning-algorithms hyperparameter-optimization artificial-neural-networks grid-search tuning-parameters knn bayesian-optimization hyperparameter-tuning random-search particle-swarm-optimization hpo python-examples python-samples hyperband
  • Updated Sep 22, 2022
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pavankalyan1997 / Machine-learning-without-any-libraries

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This is a collection of some of the important machine learning algorithms which are implemented with out using any libraries. Libraries such as numpy and pandas are used to improve computational complexity of algorithms

machine-learning-algorithms jupyter-notebook naive-bayes-classifier artificial-neural-networks k-means-clustering simple-linear-regression knn-classifier multiple-linear-regression
  • Updated Feb 5, 2019
  • Jupyter Notebook

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