Few-Shot Cross-Lingual Stance Detection with Sentiment-Based Pre-Training
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Updated
Mar 4, 2022 - Python
Few-Shot Cross-Lingual Stance Detection with Sentiment-Based Pre-Training
Atlantic: Automated Data Preprocessing Framework for Supervised Machine Learning
To predict whether booked appointment will be completed or it will be no show.
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
Machine learning algorithm is used to detect whether the person will suffer from chronic kidney disease or not.
[CIKM 2021] The source code of "Fully Hyperbolic Graph Convolution Network for Recommendation"
This project aims to predict the salary of employees based on various features using a decision tree classifier algorithm. By analyzing the provided dataset, the model can make accurate predictions if the salaries of new employees is above 100K or not.
Here are some fun projects to learn ML using Handson approach
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Machine Learning Exercise: Exploring categorical plots, LabelEncoder, pipelines and GridSearchCV using Telco Customer Churn data from Kaggle
Exploratory Data Analysis Part-2
Machine learning Classification for Family Determination for various generations by their age, height, weight, etc...
Data analysis, visualization and prediction to predict whether a patient has benign or malignant breast cancer based on properties of the cancer
CyberSoft Machine Learning 03 - Overview
Predict the Burned Area of Forest Fire with Neural Networks and Predicting Turbine Energy Yield (TEY) using Ambient Variables as Features.
Prepare a classification model using Naive Bayes for salary data
This repository contains introductory notebooks for support vector machine
Unofficial but extremely useful Label and One Hot encoders.
Assignment: ICC WorldCup 2015 PlayCricket - Decision Tree
Add a description, image, and links to the label-encoder topic page so that developers can more easily learn about it.
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