Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.

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.

Data Science Feature Engineering and Selection Tutorials

A complete A-Z guide to Machine Learning and Data Science using Python. Includes implementation of ML algorithms, statistical methods, and feature selection techniques in Jupyter Notebooks. Follow Coursesteach for tutorials and updates.

Notebook image and notebook for feature reduction talk

Interactive ML Toolset

Best for beginners | Well explained ML algorithms | organized Notebooks | Case Studies

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.

some competitions (EDA, Feature Engineering, XGBoost)

Jupyter notebook for IoT threat detection using ensemble machine learning. Features data preprocessing, model training (Logistic Regression, Decision Trees, Neural Networks, etc.), and ensemble techniques for enhanced accuracy.

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 …

This repository provides a collection of Jupyter Notebook examples demonstrating various feature selection techniques using Python.

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! 📊🚀"

Data Science Python notebooks

This is an EDA notebook

Sameer Girolkar's AIML practice Notebooks

This project is a similarity checker for academic theses, implemented using Support Vector Machine (SVM) algorithms. It aims to help detect similarities between different documents, assisting in identifying potential instances of plagiarism.

Relationship prediction between nodes using Neo4J and Jupiter Notebook

This is an EDA Notebook of Flight Price Prediction