Data Science Feature Engineering and Selection Tutorials
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Updated
May 22, 2024 - Jupyter Notebook
Data Science Feature Engineering and Selection Tutorials
Beginner-friendly collection of Python notebooks for various use cases of machine learning, deep learning, and analytics. For each notebook there is a separate tutorial on the relataly.com blog.
Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.
Interactive ML Toolset
Sameer Girolkar's AIML practice Notebooks
Explore a collection of Jupyter notebooks that guide you through various stages of the machine learning pipeline. From data analysis and feature engineering to model training and deployment, these notebooks provide practical insights for both beginners and experienced data enthusiasts. Let's dive into the world of data-driven decision-making! 📊🚀"
Relationship prediction between nodes using Neo4J and Jupiter Notebook
In this notebook, I have shed some light on some useful feature selection techniques simply you can use in Machine Learning.
This interactive notebook includes the original implementation of total cumulative mutual information (TCMI) to reproduce the main results presented in the publication "TCMI: a non-parametric mutual-dependence estimator for multivariate continuous distributions" (DOI: 10.1007/s10618-022-00847-y) (Preprint: https://arxiv.org/abs/2001.11212).
Predicting the Contraceptive Method Choice of a Woman Based on Demographic and Socio-economic Characteristics - The objective of this study is to to predict the contraceptive methods (no use, long-term methods, or short-term methods) of a woman based on her demographic and socio-economic characteristics. A data-set of 1473 married women with the…
Notebook image and notebook for feature reduction talk
A set of notebooks that leverage classical ML algorithms and DL neural nets using TF, Keras and Theano to address a series of issues in the field of conservation and biology.
Exploratory Data Analysis of Various datasets
Best for beginners | Well explained ML algorithms | organized Notebooks | Case Studies
This repository contains notebooks in which I have implemented ML Kaggle Exercises for academic and self-learning purposes. In my notebooks, I have implemented some basic processes involved in ML Data Processing like How to take care of Missing Values, Handling Categorical Variables, and operations like mapping, 'Grouping', 'Sorting', 'Renaming …
Extensive Collection of Jupyter Notebooks focused on Machine Learning covering different techniques includes Feature Engineering, Feature Selection, Feature Extraction, Model Training & Testing.
Data Science Python notebooks
This repository provides a collection of Jupyter Notebook examples demonstrating various feature selection techniques using Python.
Information gain of a car dataset was calculated in this notebook
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