This sample shows how to create a Jupyter Notebook with the interactive pivot table and pivot charts components. This approach can be used for data analysis and data visualization purposes.

In this repo I will show you how to embed your Power BI report in Python Jupyter Notebook

This repository contains all Python scripts and Jupyter Notebooks that were used in the final stages of my undergraduate thesis. To summarise, the thesis involved the analysis of Stage N2 portions of 8 hour EEG recordings across 15 patients in order to extract 'sleep spindles'. The 'Quadratic Parameter Sinusoid' or QPS (Palliyali et. al. 2015) was used as a way to extract 6 quadratic polynomial coefficients that served as statistical descriptors of features of the extracted spindles (and non-spindles) such as their amplitudes, envelope symmetry, frequency, phase and more. The way this was achieved was using non-linear least squares (NLLS) via the Levenberg-Marquadt Algorithm (LM) as a way to perform a best fit of the model to the raw captured spindle. The main goal of the thesis was to use these 6 parameters as learning features in a simple feed-forward neural network in order to classify whether or not an acquired raw portion of an EEG signal is a spindle or not. The conclusion to the study showed that while the QPS model was a great way to reconstruct spindles and extract valuable coefficient data, there is no guarantee the non-linear regression will work since parameter initialisation is highly dependent on whether or not it is known (for certain) if the acquired raw section of the EEG is a spindle or not.

This repo contains jupyter notebooks that show how to use PyTorch for various deep learning tasks, such as image classification, object detection, NLP, and more. The notebooks cover data loading, model building, training, evaluation, and advanced techniques.

This repo contains the Jupyter Notebook to show different analysis use-cases with qbeast-spark.

This repo contains jupyter notebooks which shows the true power of combined word embedding and image pattern detection.