randomizedsearchcv
There are 84 repositories under randomizedsearchcv topic.
PacktWorkshops/The-Python-Workshop
A New, Interactive Approach to Learning Python
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.
ashishrana1501/Forest-Fire-Prediction
Algerian Forest Fire Prediction
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.
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.
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'.
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
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
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.
ohmthanap/Churn-Predictions-Telecom-Customer
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.
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.
Lacerdash/Nested-Cross-Validation
Using scikit-learn RandomizedSearchCV and cross_val_score for ML Nested Cross Validation
abhijha3011/Hyper-Parameter-Optimization-Techniques
Hyper Parameter Techniques
Akanksha-tetwar/Car-Prediction
This notebook uses RandomForestRegressor to predict the re-sale value of a car.
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.
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.
dariak153/Comprasion_of_classifiers
Comparision of classifiers
DataScienceVishal/Telecom_Churn
Telecom Churn prediction with multiple machine learning models
iamkirankumaryadav/Classification
Classification Model (End to End Classification of Heart Disease - UCI Data Set)
iamkirankumaryadav/Improvement
Improving a Machine Learning Model
jesussantana/Supervised-Regression
Practice and become familiar with regressions
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
MINEEJA/Bulldozer-_price_prediction
Predicting the sale price of Bulldozers using RandomForestRegressor
rukshar69/Flight-Price-Prediction
Predict Prices for Indian Flights
SannketNikam/Credit-Risk-Analysis
Credito - Credit Risk Analysis using XGBoost Classifier with RandomizedSearchCV for loan approval decisions.
seroetr/Disaster-Tweets-with-NLP
Disaster Tweets Classifications by Machine Learning, which is a currently Kaggle Competition.
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.
Ashwin0229/Tree-Classifiers
Comparative Analysis of Decision Tree Algorithms in Number Classification: Bagging vs. Random Forest vs. Gradient Boosting Decision Tree Classifiers
DataScienceVishal/Bank_Customer_Behaviour
Bank Customer Behaviour Prediction
kgdatatech/climatewins-ml
Exploring the intersection of supervised machine learning algorithms and weather data to drive ClimateWins forward. (CF student project)
Shardy2907/House-Price-Prediction
A Machine Learning Regression Model has been used to predict the prices for houses in Boston.
aashishcoder/Parkinson-Disease-Detection
Parkinson disease detection using KNN Classifier and Random Forest Classifier.
Ayomikun17/Diabetes-Prediction-
Diabetes Prediction with Tree based models (Random Forest and XGBoost). Grid Search CV and Randomized Search CV used to optimize parameters
KumaarBalbir/HyperTuning
Different techniques to tune the hyperparameter of machine learning models.
sanhiitaa/fastag-fraud-detection-classification
Fastag Fraud Detection Classification System
shubhampundhir/Medical-Personal-Cost-Prediction
In this project the task is to predict charges or cost of the person on the basis of his/her lifestyle, smoking habit, number of children's and person's home location.