Topic: randomizedsearchcv Goto Github
Some thing interesting about randomizedsearchcv
Some thing interesting about randomizedsearchcv
randomizedsearchcv,This repository includes the implementation of RandomizedSearchCV (with cross-validation) for hyperparameter fine-tuning in Convolutional Neural Networks
User: aaolcay
randomizedsearchcv,Hyper Parameter Techniques
User: abhijha3011
randomizedsearchcv,This notebook uses RandomForestRegressor to predict the re-sale value of a car.
User: akanksha-tetwar
randomizedsearchcv,Deploying Flight Price Prediction via Microsoft Azure
User: akash1070
randomizedsearchcv,Flight Price Prediction Model Deployment IN Heroku
User: akash1070
randomizedsearchcv,A comprehensive analysis and predictive modeling of the "Salary Data.csv" dataset to forecast salaries. Utilizes advanced machine learning techniques, including pipelines and transformers, for robust and accurate predictions.
User: alavi-sam
Home Page: https://salary-prediction-brown.vercel.app
randomizedsearchcv,I have built a Model using the Random Forest Regressor of California Housing Prices Dataset to predict the price of the Houses in California.
User: amit-timalsina
randomizedsearchcv,Algerian Forest Fire Prediction
User: ashishrana1501
randomizedsearchcv,Flight Price Predictor is a service that helps you forecast the price of a flight ticket .The goal of this project, first apply the machine learning models then predict to flight price.
User: asimchakraborty
randomizedsearchcv,The ability to predict prices and features affecting the appraisal of property can be a powerful tool in such a cash intensive market for a lessor. Additionally, a predictor that forecasts the number of reviews a specific listing will get may be helpful in examining elements that affect a property's popularity.
User: astonglen
randomizedsearchcv,The project includes building seven different machine learning classifiers (including Linear Regression, Decision Tree, Bagging, Random Forest, Gradient Boost, AdaBoost, and XGBoost) using Original, OverSampled, and Undersampled data of ReneWind case study, tuning hyperparameters of the models, performance comparisons, and pipeline development for productionizing the final model.
User: ayda-darvishan
randomizedsearchcv,This project is based on a classification algorithm i.e. Naive Bayes which is run on a mobile dataset consisting of 2000 rows and 15 columns. It is a multi-class problem where mobile phones are classified in accordance with their price range. There are four classes of price ranging from 0 to 3, 0 indicating cheaper mobiles phones and 3 representing expensive mobile phones. Univariate analysis is conducted to understand individual predictors and bivariate analysis is conducted to infer relationship between predictors with other predictors and target variable. Important features are identified by Random Forest.
User: bushra-ansari
randomizedsearchcv,Telecom Churn prediction with multiple machine learning models
User: datasciencevishal
randomizedsearchcv,Repositório de classificação de Spam (Kaggle competition)
User: dbbatalha
randomizedsearchcv,The aim of this project is to develop a solution using Data science and machine learning to predict the compressive strength of a concrete with respect to the its age and the quantity of ingredients used.
User: esvs2202
Home Page: https://ccs-predictor.herokuapp.com/
randomizedsearchcv,Hyperparameter tuning using gridsearchCV and randomizedsearchCV
User: fahimabrar
randomizedsearchcv,Develop a predictive model that determines the likelihood of a customer defaulting loan payment
User: fortune-uwha
randomizedsearchcv,Modelos de classificação de risco de crédito usando algoritmos de Métodos Ensemble
User: franmateus
randomizedsearchcv,Predicting the Sale Price of Bulldozers using Machine Learning
User: hermawanhermawan
randomizedsearchcv,Model to predict bank customer churn
User: hugohiraoka
randomizedsearchcv,Classification Model (End to End Classification of Heart Disease - UCI Data Set)
User: iamkirankumaryadav
randomizedsearchcv,Improving a Machine Learning Model
User: iamkirankumaryadav
randomizedsearchcv,Regression - Bulldozer Sales Price - Kaggle Competition
User: iamkirankumaryadav
randomizedsearchcv,Practice and become familiar with regressions
User: jesussantana
randomizedsearchcv,Using scikit-learn RandomizedSearchCV and cross_val_score for ML Nested Cross Validation
User: lacerdash
randomizedsearchcv,Hyperparameter tuning is the process of finding the optimal hyperparameters for a machine learning model. Hyperparameters are values that are set prior to training a model and affect its performance, but cannot be learned from the data. Some common examples of hyperparameters include the learning rate, regularization strength.
User: mahesh3394
randomizedsearchcv,Goal Using the data collected from existing customers, build a model that will help the marketing team identify potential customers who are relatively more likely to subscribe term deposit and thus increase their hit ratio
User: maoilich
Home Page: https://github.com/MaoIlich/Project-3-Ensemble-Techniques---Term-Deposit-Sale
randomizedsearchcv,classifying a patient has a heart disease or not
User: mauryashobhit
randomizedsearchcv,factors affecting the sales of the walmart store
User: mauryashobhit
randomizedsearchcv,Flight-Price-Prediction. With this end to end Project you can able to get FliGht Ticket Fare from your place.
User: medipalletendulkar
Home Page: https://github.com/MedipalleTendulkar/Flight-Fare-Prediction
randomizedsearchcv,Predicting the sale price of Bulldozers using RandomForestRegressor
User: mineeja
randomizedsearchcv,Faces recognition project using Support Vector Machines (SVM) and Principal Component Analysis (PCA). It utilizes the Labeled Faces in the Wild (LFW) dataset, employs dimensionality reduction with PCA, and fine‑tunes SVM hyperparameters using RandomizedSearchCV.
User: mohammadshabazuddin
randomizedsearchcv,Developed a churn prediction classification model using various techniques including: EDA, Decision trees, Naive Bayes, AdaBoost, MLP, Bagging, RF, KNN, logistic regression, SVM, Hyperparameter tuning using Grid Search CV and Randomized Search CV.
User: ohmthanap
randomizedsearchcv,A New, Interactive Approach to Learning Python
Organization: packtworkshops
randomizedsearchcv,A Python Machine Learning Project designed to predict Halloween Candy sales for a company based on historical data
User: parth-kacheria
randomizedsearchcv,A Python Machine Learning project to classify the Iris Dataset
User: parth-kacheria
randomizedsearchcv,The aim to decrease the maintenance cost of generators used in wind energy production machinery. This is achieved by building various classification models, accounting for class imbalance, and tuning on a user defined cost metric (function of true positives, false positives and false negatives predicted) & productionising the model using pipelines.
User: rochitasundar
randomizedsearchcv,This project predicts wind turbine failure using numerous sensor data by applying classification based ML models that improves prediction by tuning model hyperparameters and addressing class imbalance through over and under sampling data. Final model is productionized using a data pipeline
User: rudrachatterjee
randomizedsearchcv,Predict Prices for Indian Flights
User: rukshar69
Home Page: https://rukshar69-flight-price-predi-streamlit-flight-prediction-ch3wai.streamlit.app/
randomizedsearchcv,Credito - Credit Risk Analysis using XGBoost Classifier with RandomizedSearchCV for loan approval decisions.
User: sannketnikam
Home Page: https://credito.pythonanywhere.com
randomizedsearchcv,Using Logistic Regression with RandomizedSearchCV Hyperparameter Tuning to find out whether a student gets placement or not.
User: sannketnikam
Home Page: https://placementcgpa.pythonanywhere.com/
randomizedsearchcv,This repository includes Machine Learning model on second hand car price prediction fron cardekho.com I have used RandomForest Regressor as it is best one performing on this dataset . This repository include model file which have all the implementation of model and other file is MODALUSAGE in which I have used the model I did by giving the features to predict the Price.
User: sefaamash
randomizedsearchcv,Diabetes Classification with SVM and Random Forest Classifiers
User: semmyinc
randomizedsearchcv,Disaster Tweets Classifications by Machine Learning, which is a currently Kaggle Competition.
User: seroetr
randomizedsearchcv,A comprehensive data science project for analysing eCormmerce and online shops data for possibility to enegage customer retention to increase purchases. Trained and comprehensively evaluated machine learning models using different algorithms and tuning procedures.
User: simon-157
randomizedsearchcv,This is a friend recommendation systems which are used on social media platforms (e.g. Facebook, Instagram, Twitter) to suggest friends/new connections based on common interests, workplace, common friends etc. using Graph Mining techniques. Here, we are given a social graph, i.e. a graph structure where nodes are individuals on social media platforms and a directed edges (or 'links') indicates that one person 'follows' the other, or are 'friends' on social media. Now, the task is to predict newer edges to be offered as 'friend suggestions'.
User: somjit101
randomizedsearchcv,Telecom Churn Case Study
User: soumya-mishra
randomizedsearchcv,study of hyperparameter tuning methods
User: startrexii
randomizedsearchcv,The repository contains the California House Prices Prediction Project implemented with Machine Learning. The app was deployed on the Flask server, implemented End-to-End by developing a front end to consume the Machine Learning model, and deployed in Azure, Google Cloud Platform, and Heroku. Refer to README.md for demo and application link
User: tejas-ta
Home Page: https://ai-california-house-prices.ue.r.appspot.com/
randomizedsearchcv,I have built a Model using Random Forest Regressor of California Housing Prices Dataset to predict the price of the Houses in California.
User: thinamxx
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