randomizedsearchcv

There are 95 repositories under randomizedsearchcv topic.

  • PacktWorkshops/The-Python-Workshop

    A New, Interactive Approach to Learning Python

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  • esvs2202/Concrete-Compressive-Strength-Prediction

    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.

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  • rochitasundar/Predictive-maintenance-cost-minimization-using-ML-ReneWind

    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.

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  • ashishrana1501/Forest-Fire-Prediction

    Algerian Forest Fire Prediction

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  • ThinamXx/CaliforniaHousing__Prices

    I have built a Model using Random Forest Regressor of California Housing Prices Dataset to predict the price of the Houses in California.

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  • somjit101/Facebook-Friend-Recommendation

    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'.

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  • SannketNikam/Credit-Risk-Analysis

    Credito - Credit Risk Analysis using XGBoost Classifier with RandomizedSearchCV for loan approval decisions.

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  • RudraChatterjee/Machine-Failure_Prediction_EnsembleMethods_ModelTuning

    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

    Language:Jupyter Notebook7102
  • Machine-Learning-Prediction-of-California-House-Prices

    Tejas-TA/Machine-Learning-Prediction-of-California-House-Prices

    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

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  • Ayda-Darvishan/Tuning-ML-Classifiers

    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.

    Language:Jupyter Notebook3100
  • ohmthanap/Telecom-Customer-Churn-Predictions

    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.

    Language:Jupyter Notebook3100
  • alavi-sam/salary-prediction

    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.

    Language:Jupyter Notebook2100
  • bPavan16/Used-Car-Price-Prediction

    This project was developed as an individual endeavor to predict the price of used cars based on various car attributes. Using multiple regression models

    Language:Jupyter Notebook2100
  • Lacerdash/Nested-Cross-Validation

    Using scikit-learn RandomizedSearchCV and cross_val_score for ML Nested Cross Validation

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  • abhijha3011/Hyper-Parameter-Optimization-Techniques

    Hyper Parameter Techniques

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  • Akanksha-tetwar/Car-Prediction

    This notebook uses RandomForestRegressor to predict the re-sale value of a car.

    Language:Jupyter Notebook1100
  • amit-timalsina/California-Housing-Price-Prediction

    I have built a Model using the Random Forest Regressor of California Housing Prices Dataset to predict the price of the Houses in California.

    Language:Jupyter Notebook110
  • AirBnb-Price-Prediction

    astonglen/AirBnb-Price-Prediction

    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.

    Language:Jupyter Notebook1100
  • DataScienceVishal/Telecom_Churn

    Telecom Churn prediction with multiple machine learning models

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  • Ehtisham33/Hyperparameters-Tunning-of-Machine-Learning-Models

    This project is to classify emails as spam or not spam using various machine learning models. Hyperparameter tuning is performed to optimize model performance.

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  • FrienDotJava/adult-census-income

    [Deployed in Streamlit] A machine learning project classifying whether someone has income >$50K or <$50K using several models.

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  • iamkirankumaryadav/Classification

    Classification Model (End to End Classification of Heart Disease - UCI Data Set)

    Language:Jupyter Notebook110
  • iamkirankumaryadav/Improvement

    Improving a Machine Learning Model

    Language:Jupyter Notebook1101
  • jesussantana/Supervised-Regression

    Practice and become familiar with regressions

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  • kgdatatech/climatewins-ml

    Exploring the intersection of supervised machine learning algorithms and weather data to drive ClimateWins forward. (CF student project)

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  • MaoIlich/Project-3-Ensemble-Techniques---Term-Deposit-Sale

    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

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  • Bulldozer-_price_prediction

    MINEEJA/Bulldozer-_price_prediction

    Predicting the sale price of Bulldozers using RandomForestRegressor

    Language:Jupyter Notebook1100
  • rosasbehoundja/Cryptojacking_Detection

    Cryptojacking classification

    Language:Jupyter Notebook1100
  • rukshar69/Flight-Price-Prediction

    Predict Prices for Indian Flights

    Language:Jupyter Notebook1101
  • seroetr/Disaster-Tweets-with-NLP

    Disaster Tweets Classifications by Machine Learning, which is a currently Kaggle Competition.

    Language:Jupyter Notebook1100
  • Simon-157/AI-final-project

    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.

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  • Ehsan-Behzadi/Breast-Cancer-Prediction-Model

    This project implements a machine learning model to predict breast cancer diagnosis. Utilizing techniques such as data preprocessing, feature selection, and various algorithms, the model aims to assist in early detection and improve healthcare outcomes. Explore the repository to understand the methodology and technologies used in this project.

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  • GaneshAhire30/Big_Mart_Sales_Prediction-Project

    Big Mart Sales Prediction is a machine learning project that predicts product sales across multiple stores using features like item price, weight, and store type. The model uses regression techniques to help optimize inventory and sales strategies.

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  • maheera421/Bulldozer-Price-Prediction-Model

    Prediction of the auction prices of bulldozers using historical data.

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  • MohamedLotfy989/Credit-Card-Fraud-Detection

    This repository focuses on credit card fraud detection using machine learning models, addressing class imbalance with SMOTE & undersampling, and optimizing performance via Grid Search & RandomizedSearchCV. It explores Logistic Regression, Random Forest, Voting Classifier, and XGBoost. balancing precision-recall trade-offs for fraud detection.

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  • Prakshi-23/placement_ml_project

    🚀 Built a Placement Prediction System using machine learning to analyze student data and predict placement chances. Achieved 81.05% accuracy with AdaBoost and deployed a Streamlit app for real-time predictions.

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