Time-series Data Preprocessing Studio in Jupyter notebook.

Notebooks for preprocessing and analysis of Planetscope 4 band data/imagery, using rasterio and fiona.

A notebook on visualizing and preprocessing of the EEG signals

Scripts and notebooks for pre-processing jet data into different formats, primarily the jet-image and Lund plane formats. The focus is on datasets used in the Landscape of Top Taggers challenge.

ML Basics through examples

My notes over the course of different experiences in Machine Learning with some useful snippets I learnt in Python3.

Jupyter Notebooks for the MOHID Water Modelling System

PSO feature selection improves classifier performance. Implemented in Jupyter Notebook with pandas, numpy, scikit-learn. PSO done from scratch. Results compared using accuracy, precision, recall, F1 score. Improves results compared to using all features. Can be applied to various classification problems.

Several notebooks that contain different functions implemented in Python to understand the basic steps to carry out a machine learning problem.

This repository will explain a set of data mining labs to make you familiar with the machine learning process.

Scripts used to transform our data before importing to jupyter notebook and tensorflow. Mainly used to match our data with satellite imagery

Implements a genetic algorithm to select the most impactful features in a dataset to improve classifier performance. Written in Jupyter Notebook using pandas, numpy, scikit-learn. Results displayed with accuracy, precision, recall, F1 score comparison to using all features.

Identification of brain tumour at a premature stage offers a opportunity of effective medical treatment. For this purpose, the present notebook is an application of deep learning and transfer learning for brain tumor detection using keras from Tensorflow framework.

This repository contains a Jupyter notebook for building an anime recommendation system using various machine learning models. The notebook includes steps for data preprocessing, feature extraction, model training, and creating a user-friendly graphical user interface (GUI) with tkinter.

I used this notebook to discuss different supervised learning approaches. In the notebook you can find evaluations of a logistic regression, a K-Nearest-Neighboor, a Support Vector Machine, a Decision Tree and the ensemble methods Random Forest, AdaBoost and XGBoost Classifyer.

This notebook analyses the word frequency in the novel Moby Dick. It illustrates a general-purpose NLP pre-processing pipeline.

Welcome to the Machine Learning Repository! This repository houses a collection of notebooks focused on machine learning projects, feature engineering, and feature selection techniques. Whether you are a beginner or an experienced data scientist, this repository offers valuable insights and implementations to enhance your machine learning skills.

This repository consists of a Jupiter notebook showing the experiments conducted to create an RNN LSTM Model. Also, it shows the prediction done on the collected data from Twitter.

Scripts and notebooks for pre-processing di-jet event data into different formats, primarily the jet-image and Lund plane formats. The focus is on the LHC Olympics 2020 datasets.