IDB-FOR-DATASCIENCE/Unsupervised-ML-Modelling-for-Segmentation

Stars
8
Rank 2,099,232 (Top 42 %)
Language
Jupyter Notebook
License
MIT License
Created about 4 years ago
Updated over 3 years ago

IDB-FOR-DATASCIENCE/Unsupervised-ML-Modelling-for-Segmentation

IDB-FOR-DATASCIENCE

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Python Implementation of multiple unsupervised segmentation models and evaluating them through multiple evaluation metrics

Predictive-Excellence-Engine

In this notebook, we will create an AI and time serie driven forecasting engine based on a set of 5 AI models and 5 time series models and employ several algorithms to perform feature engineering and selection on a multivariate time series dataset.

Jupyter Notebook

ML-based-feature-selection

This notebook is a one stop shop for ML based feature selection for classification purpose. Once the master data is prepared, we can use this notebook to try out 8 feature selection techniques and combine their results

Jupyter Notebook

Data-Scientist-for-Enterprise-Nanodegree-Program

This repository has the solutions to multiple assignments done during the course on topics like supervised leering, deep learning

Jupyter Notebook

Predicting-fit-of-a-candidate-for-a-job-using-tree-based-models

We use multiple Tree boosting models and compare their performance to calculate the fit percentage of a candidate for the job they apply for. Also try to handle categorical methods using various methods.

Jupyter Notebook

Model-Monitoring

Let's talk Precision, Recall, F1 score, Reject Rate, PSI, CSI, KS and Gini along with their python implementation

Jupyter Notebook

Deep_Learning

Code base for trying various DL models

Jupyter Notebook