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srafay / Machine_Learning_A-Z

Star 358

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

NishkarshRaj / 100DaysofMLCode

Sponsor
Star 313

My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge. Now supported by bright developers adding their learnings 👍

python machine-learning big-data deep-learning linear-regression linear-algebra regression artificial-intelligence neural-networks classification artificial-neural-networks polynomial-regression regression-models hacktoberfest clustering-algorithm 100daysofcode scikitlearn-machine-learning classification-algorithm 100daysofmlcode github-actions
  • Updated Aug 18, 2023
  • Jupyter Notebook

arnaldog12 / Machine_Learning

Star 212

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 27, 2022
  • Jupyter Notebook

MBKraus / Predicting_real_estate_prices_using_scikit-learn

Star 148

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

Star 81

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 Dec 8, 2023
  • Jupyter Notebook

elcorto / pwtools

Star 60

pwtools is a Python package for pre- and postprocessing of atomistic calculations, mostly targeted to Quantum Espresso, CPMD, CP2K and LAMMPS. It is almost, but not quite, entirely unlike ASE, with some tools extending numpy/scipy. It has a set of powerful parsers and data types for storing calculation data.

python sqlite molecular-dynamics lammps preprocessing quantum-espresso polynomial-regression cp2k multivariate-regression radial-basis-function kernel-regression postprocessing radial-distribution-function ase parameter-sweep kernel-ridge-regression quasi-harmonic-approximation cpmd radial-pair-correlation-function
  • Updated Aug 28, 2023
  • Python

eaglewarrior / Machine-learning

Star 42

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 datascience model-selection neural-networks polynomial-regression hacktoberfest hacktober nlp-machine-learning prediction-model logisitic-regression decision-tree-regression customer-segmentation random-forest-regression hactoberfest-accepted
  • Updated Feb 7, 2024
  • Jupyter Notebook
synthetic_well-log_polynomial_regression

abhishekdbihani / synthetic_well-log_polynomial_regression

Star 30

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

anishsingh20 / Statistical-Learning-using-R

Star 30

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
mida

srohit0 / mida

Sponsor
Star 25

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

MeghnathReddy / Concrete-Compressive-Strength-Prediction

Star 17

Different modeling techniques like multiple linear regression, decision tree, and random forest, etc. will be used for predicting the concrete compressive strength. A comparative analysis will be performed to identify the best model for our prediction in terms of accuracy. The best model will be helpful for civil engineers in choosing the approp…

linear-regression exploratory-data-analysis scatter-plot decision-trees polynomial-regression laso correlation-matrix error-prediction modeling-approach
  • Updated Jul 28, 2020
  • Jupyter Notebook

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