Machine Learning Exercise: Exploring categorical plots, LabelEncoder, pipelines and GridSearchCV using Telco Customer Churn data from Kaggle
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Updated
Sep 30, 2019 - Jupyter Notebook
Machine Learning Exercise: Exploring categorical plots, LabelEncoder, pipelines and GridSearchCV using Telco Customer Churn data from Kaggle
Assignment: ICC WorldCup 2015 PlayCricket - Decision Tree
Exploratory Data Analysis Part-2
Unofficial but extremely useful Label and One Hot encoders.
Machine learning algorithm is used to detect whether the person will suffer from chronic kidney disease or not.
Supervised-ML-Decision-Tree-C5.0-Entropy-Iris-Flower-Using Entropy Criteria - Classification Model. Import Libraries and data set, EDA, Apply Label Encoding, Model Building - Building/Training Decision Tree Classifier (C5.0) using Entropy Criteria. Validation and Testing Decision Tree Classifier (C5.0) Model
To predict whether booked appointment will be completed or it will be no show.
Prepare a classification model using Naive Bayes for salary data
Data analysis, visualization and prediction to predict whether a patient has benign or malignant breast cancer based on properties of the cancer
Few-Shot Cross-Lingual Stance Detection with Sentiment-Based Pre-Training
Feature Engineering on Time Series Dataset (Flight Price Prediction)
Desafio do titanic para classificação se tal pessoa morreria ou sobreviveria
GridSearchCV For Model optimization
This repository contains introductory notebooks for support vector machine
Prepare a classification model using Naive Bayes for salary data.
Repositório com pratica de ETL
Predict the Burned Area of Forest Fire with Neural Networks and Predicting Turbine Energy Yield (TEY) using Ambient Variables as Features.
Diamond Price Prediction Using Machine Learning (Regression Use Case)
ExcelR_Assignment---Naive-Byes---Assignment---12
We build a model to predict the value of used cars, while also considering speed and quality of the prediction.
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