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JuzerShakir / Predicting_Boston_Housing_Prices

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Builded a model to predict the value of a given house in the Boston real estate market using various statistical analysis tools. Identified the best price that a client can sell their house utilizing machine learning.

machine-learning numpy sklearn pandas python3 supervised-learning matplotlib data-exploration udacity-nanodegree boston-housing-price-prediction model-evaluation bias-variance k-fold model-validation decision-tree-regression mlfnd gridsearchcv r2-score
  • Updated Oct 4, 2018
  • HTML

wlodpawlowski / machine-learning-basic-datasets

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Repository which consists different code snippets and projects for my personal lessons recorded at the University of San Francisco in during learning of the Machine Learning.

machine-learning random-forest machine-learning-algorithms ml logistic-regression machine-learning-library regularization gradient-descent rf data-preparation nlp-machine-learning model-validation machine-learning-models machine-learning-practice machine-learning-mathematics machine-learning-a-to-z data-products machine-learning-model machine-learning-mo building-data-products
  • Updated May 1, 2019
Predicting-Boston-Housing-Prices

sushant1827 / Predicting-Boston-Housing-Prices

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Machine Learning Nano-degree Project : To assist a real estate agent and his/her client with finding the best selling price for their home

python machine-learning scikit-learn cross-validation model-selection housing-prices boston regression-models boston-housing-price-prediction learning-curve scikitlearn-machine-learning model-validation complexity-analysis model-complexity boston-housing-prices decision-tree-regression boston-housing-dataset gridsearchcv complexity-curve matplotlib-pyplot
  • Updated Oct 17, 2019
  • Jupyter Notebook

subhayuroy / Melbourne_HousingAnalysis

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Predicting the price of any 🏚house🏡 in Melbourne, Australia🌏by tracing through the decision tree🌳, always picking the path corresponding to that house's characteristics🏘. The predicted price💰 for the house is at the bottom of the tree. The point at the bottom where we make a prediction is called a leaf🍀

random-forest decision-tree model-validation missing-values underfitting-overfitting
  • Updated Aug 26, 2020
  • Jupyter Notebook

vaitybharati / P36.-Supervised-ML---Decision-Tree---C5.0-Entropy-Iris-Flower-

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Supervised-ML-Decision-Tree-C5.0-Entropy-Iris-Flower-Using Entropy Criteria - Classification Model. Import Libraries and data set, EDA, Apply Label Encoding, Model Building - Building/Training Decision Tree Classifier (C5.0) using Entropy Criteria. Validation and Testing Decision Tree Classifier (C5.0) Model

python entropy numpy sklearn matplotlib decision-trees decision-tree-classifier classification-report model-validation model-building sklearn-dataset model-testing train-test-split sklearn-tree label-encoder
  • Updated Nov 9, 2021
  • Jupyter Notebook

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