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MBKraus / Predicting_real_estate_prices_using_scikit-learn

Star 159

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

Sarvandani / Machine_learning-deep_learning_11_algorithms-of-regression

Star 10

sklearn, tensorflow, random-forest, adaboost, decision-tress, polynomial-regression, g-boost, knn, extratrees, svr, ridge, bayesian-ridge

machine-learning kernel deep-learning random-forest sklearn bayesian adaboost decision-trees polynomial-regression keras-tensorflow gradient-boosting knn-regression regression-algorithms extratrees svr-regression-prediction
  • Updated Jul 13, 2023
  • Jupyter Notebook

salihkilicli / Python-Data-Science-and-Machine-Learning-Bootcamp-Projects

Star 8

My solutions to projects given in the Udemy course: Python for Data Science and Machine Learning Bootcamp by Jose Portilla

machine-learning spark deep-learning random-forest tensorflow numpy svm linear-regression scikit-learn plotly keras pandas seaborn pyspark neural-networks logistic-regression matplotlib decision-trees kmeans-clustering knn-regression
  • Updated Oct 14, 2020
  • Jupyter Notebook

ankitAMD / NYTaxi_XG_Boost_Challenge-kaggle_challenge

Star 6

I'm attempting the NYC Taxi Duration prediction Kaggle challenge. I'll by using a combination of Pandas, Matplotlib, and XGBoost as python libraries to help me understand and analyze the taxi dataset that Kaggle provides. The goal will be to build a predictive model for taxi duration time. I'll also be using Google Colab as my jupyter notebook.…

python machine-learning deep-learning random-forest numpy linear-regression scikit-learn pandas python3 kaggle-competition xgboost matplotlib feature-engineering knn-regression xgboost-model nyc-taxi-dataset fastest-routes visualization-image google-colab remote-server
  • Updated Sep 21, 2018
  • Jupyter Notebook

mukulsinghal001 / USA-Housing-Price-Prediction

Star 4

In this project I have implemented 14 different types of regression algorithms including Linear Regression, KNN Regressor, Decision Tree Regressor, RandomForest Regressor, XGBoost, CatBoost., LightGBM, etc. Along with it I have also performed Hyper Paramter Optimization & Cross Validation.

linear-regression cross-validation regression hyperparameter-optimization knn-regression xgboost-algorithm decision-tree-regression regression-algorithms regression-analysis linearregression regression-model
  • Updated Feb 14, 2021
  • Jupyter Notebook

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