Easy pipelines for pandas DataFrames.
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Move fast from data science prototype to pipeline. Capture, analyze, and transform messy notebooks into data pipelines with just two lines of code.
The repository host gives no description.
IPython notebooks on Gilbert Strang's MIT course on linear algebra (18.06)
food image to recipe with deep convolutional neural networks.
- convolutional-neural-networks
- keras
- chef
- deep-learning
Slides, scripts and materials for the Machine Learning in Finance Course at NYU Tandon, 2022
- coursework
- fraud-detection
- introduction-to-machine-learning
- machine-learning
Fusing Histology and Genomics via Deep Learning - IEEE TMI
- pathomic
- fusion
- multimodal
- pathology
An OCaml kernel for Jupyter (IPython) notebook
- ocaml
- functional-programming
- jupyter-kernels
- machine-learning
Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.
- disentanglement
- drug-discovery
- genomics
- perturbation
A collection of tasks to probe the effectiveness of protein sequence representations in modeling aspects of protein design
- protein
- protein-sequences
- protein-design
- representation-learning
Integrated pipeline for multiplexed image analysis
- multiplexed-imaging
- python
PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturbations at bulk and single-cell levels.
BulkFormer: A large-scale foundation model for human bulk transcriptomes
a nose plugin for finding and running IPython notebooks as nose tests
Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications
- cell-annotation
- multiplexed-imaging
- mpif
Using ag-Grid in Jupyter notebooks.
Cell and line magic for PGF/TikZ-to-SVG rendering in Jupyter notebooks
The repository host gives no description.
CancerFoundation: A single-cell RNA sequencing foundation model to decipher drug resistance in cancer
- cancer
- foundation-model
- single-cell
Deciphering cell-cell communication from spatially resolved transcriptomic data at single-cell resolution with subgraph-based attentional graph neural network
Compiles Transportation Speed and Ridership Data
Attempt at reproducing a SGNN's projection layer, but with word n-grams instead of skip-grams. Paper and more: http://aclweb.org/anthology/D18-1105
Bringing Wardley Map magic to Jupyter notebooks
- wardley-maps
- wardleymaps
- python
- jupyter
A coding exercise: let's convert dirty machine learning code into clean code using a Pipeline - which is the Pipe and Filter Design Pattern applied to Machine Learning.