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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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COVID19-Literature-Clustering

MaksimEkin / COVID19-Literature-Clustering

Star 93

An approach to document exploration using Machine Learning. Let's cluster similar research articles together to make it easier for health professionals and researchers to find relevant research articles.

machine-learning random-forest clustering sklearn kaggle pca classification dimensionality-reduction bokeh kmeans tsne principal-component-analysis kmeans-clustering sgd-classifier coronavirus covid-19
  • Updated Nov 2, 2021
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sharmaroshan / MNIST-Using-K-means

Star 13

It is One of the Easiest Problems in Data Science to Detect the MNIST Numbers, Using a Classification Algorithm, Here I have used a csv File which contains the Pixels of the Numbers from 0 to 9 and we have to Classify the Numbers Accordingly. I have Used K-Means Classification Algorithm.

python machine-learning tutorial kmeans beginner jupyter-notebooks unsupervised-learning clustering-analysis imagery-analysis
  • Updated Aug 19, 2019
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Mariaorabi / Machine-learning-products-prediction

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This dataset from "ShufersalML" captures customer order history, aiming to predict future purchases using Python. It involves interconnected files that detail customer orders over time. The goal is to build a predictive model leveraging past order patterns to anticipate which products a user is likely to include in their next order.

python machine-learning random-forest prediction pca kmeans adaboost gmm knn kmeans-clustering prediction-model gradient-boosting visulization juypter-notebook
  • Updated Nov 19, 2023
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SANTONLA / INTRODUCTION-TO-MACHINE-LEARNING-WITH-R

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This is a repository with exercises extracted from the book "Introduction to machine learning with R" from Scott V. Burger. It will help you gain a solid foundation in machine learning principles. Using the R programming and then move into more advanced topics such as neural networks and tree-based methods.

machine-learning random-forest regression neural-networks classification kmeans support-vector-machines tree-based-methods
  • Updated Dec 31, 2022
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