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srafay / Machine_Learning_A-Z

Star 384

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

pavankalyan1997 / Machine-learning-without-any-libraries

Star 185

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

vaitybharati / Assignment-04-Simple-Linear-Regression-2

Star 9

Assignment-04-Simple-Linear-Regression-2. Q2) Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization. Correlation Analysis. Model Building. Model Testing. Model Predictions.

python numpy smf eda pandas data-visualization seaborn p-value model-predictions feature-engineering ols-regression statsmodels model-building simple-linear-regression correlation-analysis t-score model-testing distplot regression-plot r-square-values
  • Updated May 30, 2021
  • Jupyter Notebook

PayThePizzo / Predictive-Analysis-Notes

Star 5

Predictive Analysis Course's notes for Computer Science B.S. at Ca' Foscari University of Venice

r statistics rstudio transformations variable-selection influence statistical-analysis model-selection data-visualisation classification data-analysis glm prediction-model generalized-linear-models residuals categorical-data simple-linear-regression collinearity-diagnostics multiple-linear-regression collinearity
  • Updated Mar 2, 2024
  • HTML

Joycechidi / MachineLearning

Star 5

All my Machine Learning Projects from A to Z in (Python & R)

python r naive-bayes regression classification logistic-regression polynomial-regression decision-tree-regression kernel-svm simple-linear-regression random-forest-regression multiple-linear-regression datapreprocessing support-vector-regression--svr evaluating-regression-models-perf regularization-methods k-nearest-neighbors-k-nn support-vector-machine-svm decision-tree-classification random-forest-classification
  • Updated Aug 15, 2019
  • Jupyter Notebook

Avinash793 / regression-analysis-examples

Star 3

Detailed implementation of various regression analysis models and concepts on real dataset.

python3 outliers autocorrelation feature-engineering goodness-of-fit regression-diagnostics multicollinearity quantile-regression residuals regression-analysis simple-linear-regression poisson-regression-model heteroskedasticity leverages q-q-plot multiple-linear-regression-model ols-regression-model cooks-distance influential-cases gls-regression-model
  • Updated Jan 15, 2024
  • Jupyter Notebook

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