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MBKraus / Predicting_real_estate_prices_using_scikit-learn

Star 157

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

ibodumas / my_KNN_PCA_MNIST

Star 3

Problems Identification: This project involves the implementation of efficient and effective KNN classifiers on MNIST data set. The MNIST data comprises of digital images of several digits ranging from 0 to 9. Each image is 28 x 28 pixels. Thus, the data set has 10 levels of classes.

mnist pca-analysis pca mnist-classification knn-search knn mnist-data knn-graphs knn-matting knn-algorithm-proof mnist-nn mnist-classifier nn-predictive-control mnist-model knn-regression knn-classification knn-model mnist-handwriting-recognition knn-classifier
  • Updated Oct 30, 2017
  • Jupyter Notebook

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