Customer Churn Dataset Analysis
Machine Learning, EDA, Classification tasks, Regression tasks for customer churn
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Eda_nlp | 1,405 | a year ago | 9 | Python | ||||||
| Data augmentation for NLP, presented at EMNLP 2019 | ||||||||||
| Data Science Toolkit | 185 | 2 years ago | 1 | HTML | ||||||
| Collection of stats, modeling, and data science tools in Python and R. | ||||||||||
| Students Performance Analytics | 24 | 4 years ago | gpl-3.0 | Jupyter Notebook | ||||||
| Students Performance Evaluation using Feature Engineering, Feature Extraction, Manipulation of Data, Data Analysis, Data Visualization and at lat applying Classification Algorithms from Machine Learning to Separate Students with different grades | ||||||||||
| Df_cloud_type_classification | 21 | 5 years ago | Python | |||||||
| Machine Learning | 17 | 4 months ago | Jupyter Notebook | |||||||
| A set of jupyter notebooks | ||||||||||
| Twitter Sentiment Analysis | 12 | 5 years ago | gpl-3.0 | Jupyter Notebook | ||||||
| It is a Natural Language Processing Problem where Sentiment Analysis is done by Classifying the Positive tweets from negative tweets by machine learning models for classification, text mining, text analysis, data analysis and data visualization | ||||||||||
| Octopus Ml | 12 | a year ago | 13 | October 15, 2022 | 2 | mit | Jupyter Notebook | |||
| A collection of handy ML and data visualization and validation tools. Go ahead and train, evaluate and validate your ML models and data with minimal effort. | ||||||||||
| Restaurant Reviews Analysis | 10 | 5 years ago | gpl-3.0 | Jupyter Notebook | ||||||
| Using Natural Language Processing and Bag of Words for feature extraction for sentiment analysis of the customers visited in the Restaurant and at last using Classification algorithm to separate Positive and Negative Sentiments. | ||||||||||
| Insurance Claim Prediction | 10 | 5 years ago | gpl-3.0 | Jupyter Notebook | ||||||
| In this Data set we are Predicting the Insurance Claim by each user, Machine Learning algorithms for Regression analysis are used and Data Visualization are also performed to support Analysis. | ||||||||||
| Churn Modelling Dataset | 10 | 5 years ago | gpl-3.0 | Jupyter Notebook | ||||||
| Predicting which set of the customers are gong to churn out from the organization by looking into some of the important attributes and applying Machine Learning and Deep Learning on it. | ||||||||||
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Python
Machine Learning
Dataset
Classification
Eda
Linear Regression