Peax is a tool for interactive visual pattern search and exploration in epigenomic data based on unsupervised representation learning with autoencoders
- epigenomics
- pattern-search
- data-visualization
- interactive-machine-learning
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Peax is a tool for interactive visual pattern search and exploration in epigenomic data based on unsupervised representation learning with autoencoders
Various Jupyter notebooks about Common Crawl data
Research experiments exploring uncommon quant techniques.
Exercises for the lecture "Selected Topics in Audio Signal Processing"
Simple demo of filtering signal with an LPF and plotting its Short-Time Fourier Transform (STFT) and Laplace transform, in Python.
Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications
A ChatGPT-based tool to decode Jupyter notebooks and the similar python notebook environments like Google Colab, etc.
Using ag-Grid in Jupyter notebooks.
Repository for paper scMulan: a multitask generative pre-trained language model for single-cell analysis.
Cell and line magic for PGF/TikZ-to-SVG rendering in Jupyter notebooks
Jupyterlab extension to show notebook cell completion notifications
Classification and Gradient-based Localization of Chest Radiographs using PyTorch.
A jupyterlab extension to email notebooks directly from JupyterLab.
The repository host gives no description.
Gaussian processes and Bayesian optimization for images and hyperspectral data
A notebook app integrated with todo lists utility. Developed with Rust, WebAssembly, Yew and Trunk.
High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations
Open Matrix (OMX)
Tools for drawing 2d and 3d interactive visualizations using Jupyter proxy widgets
The repository host gives no description.
Deep learning model for single-cell inference of multi-omic profiles from a single input modality.
open source E-book on statistical physics
Mobile Deep Learning Projects, published by Packt
This project presents a Python-based spam detector program that utilizes the Naive Bayes approach to classify emails as either spam or ham. The system is designed to accurately and efficiently identify spam messages, providing a useful tool for individuals and organizations seeking to manage their email inboxes more effectively.