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arnaldog12 / Machine_Learning

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Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.

python machine-learning neural-network naive-bayes linear-regression machine-learning-algorithms regression feature-selection logistic-regression kmeans adaboost decision-trees polynomial-regression knn principal-component-analysis redes-neurais-artificiais linear-discriminant-analysis multilinear-regression
  • Updated Apr 11, 2021
  • Jupyter Notebook

srafay / Machine_Learning_A-Z

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Learning to create Machine Learning Algorithms

machine-learning-algorithms datascience naive-bayes-classifier logistic-regression support-vector-machine polynomial-regression decision-tree-classifier dataprocessing classification-algorithims random-forest-regressor support-vector-regression multiple-regression decision-tree-regression k-means-implementation-in-python k-means-clustering kernel-svm random-forest-classifier simple-linear-regression k-nearest-neighbors machine-learning-az
  • Updated Jun 15, 2021
  • Python

MBKraus / Predicting_real_estate_prices_using_scikit-learn

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Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)

real-estate python machine-learning neural-network random-forest lasso xgboost polynomial ensemble-learning ols decision-trees ridge-regression polynomial-regression knn multi-layer-perceptron amsterdam predicting-housing-prices lasso-regression mlp-regressor knn-regression
  • Updated Apr 9, 2019
  • Python

agrawal-priyank / machine-learning-regression

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Built house price prediction model using linear regression and k nearest neighbors and used machine learning techniques like ridge, lasso, and gradient descent for optimization in Python

python machine-learning linear-regression coursera gradient-descent ridge-regression polynomial-regression university-of-washington house-price-prediction multiple-regression machine-learning-regression
  • Updated Jan 20, 2018
  • Jupyter Notebook

anishsingh20 / Statistical-Learning-using-R

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This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.

r machine-learning-algorithms statistical-learning datascience data-analysis logistic-regression regularization decision-trees predictive-modeling polynomial-regression clustering-algorithm svm-classifier k-nn boosting generalized-additive-models supervised-machine-learning bagging depth-interpretation discriminant-anlaysis
  • Updated Apr 7, 2018
  • R

eaglewarrior / Machine-learning

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This repository will contain all the stuffs required for beginners in ML and DL do follow and star this repo for regular updates

machine-learning algorithm deep-learning clustering linear-regression probability datascience model-selection naive-bayes-classifier neural-networks polynomial-regression hacktoberfest nlp-machine-learning prediction-model logisitic-regression decision-tree-regression customer-segmentation random-forest-regression hacktoberfest2020
  • Updated Mar 29, 2021
  • Jupyter Notebook
mida

srohit0 / mida

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Selected problems and their solutions from the book on "Machine Intelligence in Design Automation"

machine-learning deep-neural-networks deep-learning neural-network machine-learning-algorithms artificial-intelligence artificial-neural-networks logistic-regression feedforward-neural-network polynomial-regression vlsi machine-intelligence design-automation electronic-design-automation vlsi-circuits vlsi-design vlsi-machine-learning vlsi-deep-learning
  • Updated Dec 9, 2018
  • Jupyter Notebook
synthetic_well-log_polynomial_regression

abhishekdbihani / synthetic_well-log_polynomial_regression

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This project attempts to construct a missing well log from other available well logs, more specifically an NMR well log from the measured Gamma Ray (GR), Caliper, Resistivity logs and the interpreted porosity from a well.

feature-selection nmr feature-engineering polynomial-regression petroleum petrophysics well-logs porosity nmr-log walker-ridge keathley-canyon resistivity-log
  • Updated Sep 21, 2020
  • Jupyter Notebook

S-B-Iqbal / Predicting-Power-Output-of-a-combined-cycle-power-plant.

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The objective of the Project is to predict ‘Full Load Electrical Power Output’ of a Base load operated combined cycle power plant using Polynomial Multiple Regression. Concepts : 1) Clustering, 2) Polynomial Regression, 3) LASSO, 4) Cross-Validation, 5) Bootstrapping

cross-validation lasso silhouette polynomial-regression bootstrapping-statistics k-means-clustering
  • Updated Sep 22, 2018
  • Jupyter Notebook

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