Topic: grid-search-cv Goto Github
Some thing interesting about grid-search-cv
Some thing interesting about grid-search-cv
grid-search-cv,Using a dataset provided by Airbnb, analysis and predictions will be made to understand what effects the total price of an Airbnb
User: ahing
grid-search-cv,Learning Machine Learning Through Data
User: akash1070
grid-search-cv,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
grid-search-cv,Programming assignments covering fundamentals of machine learning and deep learning. These were completed as part of the Plaksha Tech Leaders Fellowship program.
User: ankit-kumar-saini
grid-search-cv,Diabetes Prediction with Tree based models (Random Forest and XGBoost). Grid Search CV and Randomized Search CV used to optimize parameters
User: ayomikun17
grid-search-cv,A machine learning model built to predict if a credit card application will get approved.
User: copev313
grid-search-cv,Implented ridge and lasso regression by understanding the use of parameters
User: davityak03
grid-search-cv,Week 14 - Multiple Linear Regression and Logistic Regression
User: existentialplantperson
grid-search-cv,Building Machine Learning and ETL Pipelines to categorize emergency messages based on the needs communicated by the sender
User: faisal-aldhuwayhi
grid-search-cv,In the digital music era, understanding artist popularity on Spotify is vital. This project taps into Spotify's data, analyzing key factors driving artist prominence. Through our insights, we illuminate what sets successful artists apart in this dynamic platform.
User: gunturwibawa
grid-search-cv,Jupyter notebook using machine learning techniques to explore the complex drivers of modern slavery. Models from a research paper are replicated and evaluated . Actions also include filling missing data, training regression models, and analyzing feature importance.
User: lefteris-souflas
grid-search-cv,Disaster response project that implements data engineering tactics to classify messages sent during a real-world disaster. This project uses ETL and ML pipelines and uses the Flask library to deploy the final result on a website.
User: maltarouti
grid-search-cv,Analyze and Build a machine learning (ML) model on the Iris Flower dataset
User: maltarouti
grid-search-cv,Identify the most efficient machine learning model to identify potential donors. Project covers Linear Regression, Perceptron Algorithm, Decision Trees, Naive Bayes, Support Vector Machines and Ensemble Methods.
User: niklas-joh
grid-search-cv,Classify music into genres by classical machine learning models
User: ofir-frd
grid-search-cv,A repo packed with common and important machine learning techniques and algorithm implementations using sklearn.
User: prithvimurjani
grid-search-cv,RTA severity predictor is an application which predicts the severity of road traffic accident, so as to pave the way for improving the safety level of road traffic.
User: priyeshdave
grid-search-cv,In this project, a regression-based performance prediction model was developed to estimate building energy consumption based on simplified façade attribute information and weather conditions.
User: priyeshdave
grid-search-cv,
User: seghelicious
grid-search-cv,Forecasting Netflix Customer Retention based on Gaussian Process Regression
User: shahriar-rahman
grid-search-cv,Use decision trees to prepare a model on fraud data. Treating those who have taxable income <= 30000 as "Risky" and others are "Good" and A cloth manufacturing company is interested to know about the segment or attributes causes high sale.
User: shanuhalli
grid-search-cv,Prepare a model for glass classification using KNN and Implement a KNN model to classify the animals in to categorie.
User: shanuhalli
grid-search-cv,Use Random Forest to prepare a model on fraud data. Treating those who have taxable income <= 30000 as "Risky" and others are "Good" and A cloth manufacturing company is interested to know about the segment or attributes causes high sale.
User: shanuhalli
grid-search-cv,This repo has been developed for the Istanbul Data Science Bootcamp, organized in cooperation with İBB and Kodluyoruz. Prediction for house prices was developed using the Kaggle House Prices - Advanced Regression Techniques competition dataset.
User: uzunb
grid-search-cv,
User: zauverer
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