GitHub topics: onehotencoder
Soumyapro/Car-Price-Prediction
This project presents a comprehensive car price prediction model using machine learning techniques. The dataset is carefully explored and preprocessed, including handling missing values, encoding categorical features, and scaling numerical data. Visualizations are provided to understand key relationships and trends in car features and prices.
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mustafadanabasi/Python-OneHotEncoder-Sample
OneHotEncoder : Kategorik verileri "binary" (0 ve 1) sütunlarına ayırır. Her benzersiz kategori için ayrı bir sütun oluşturur. Özellikle sıralı olmayan kategorik değişkenler için uygundur.
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EPSOFT/Embedding
Embedding
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Khushi130404/Titanic_Pipeline
This project predicts whether a person survived the Titanic disaster based on various features using machine learning. It utilizes pipelines, ColumnTransformer, and model serialization for efficient processing and prediction.
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fayzi-dev/scikit_learn
scikit_learn
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harmanveer-2546/Ad-Click-Prediction-Analysis-and-Insights
To predict whether a user will click on ad or not.
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harmanveer-2546/Finding-you-next-perfect-house
In this exploratory data analysis, we compare a dataset which consists of various features about renting of houses available on these renting platforms listed by owners of these houses, and try to derive some constructive conclusions by performing Descriptive statistics of the available features.
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amangelbhullar/Machine-learning-Data_Cleaning_Tools-supervised-learning
Data cleaning tools, handling missing data, categorical data, feature scaling
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iamkirankumaryadav/Predictive-Analytics
Predictive Analytics
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iamkirankumaryadav/Car-Price-Prediction
Car Price Prediction
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lingumd/Neural_Network_Charity_Analysis
Machine learning and neural networks used to create a binary classifier capable of predicting whether applicants will be successful if funded by Alphabet Soup.
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twigikit/neural-network-homework
Create a binary classification model using a deep neural network
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nani757/Pipelines
pipelines chains together multiple steps so that the output of each step is used as input to the next step
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