🍇 GRAPE is a Rust/Python Graph Representation Learning library for Predictions and Evaluations
- graph
- high-performance
- machine-learning
- knowledge-graph
Repository Index
47,133 repositories indexed
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A series of machine learning tutorials for Torch7
food image to recipe with deep convolutional neural networks.
- convolutional-neural-networks
- keras
- chef
- deep-learning
Mostly experiments based on "Advances in financial machine learning" book
Slides, scripts and materials for the Machine Learning in Finance Course at NYU Tandon, 2022
- coursework
- fraud-detection
- introduction-to-machine-learning
- machine-learning
Cleora AI is a general-purpose open-source model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data. Created by Synerise.com team.
- ai
- graphs
- synerise
- embeddings
Python package for Bayesian Machine Learning with scikit-learn API
- python
- bayesian-machine-learning
- machine-learning
- scikit-learn
bert-loves-chemistry: a repository of HuggingFace models applied on chemical SMILES data for drug design, chemical modelling, etc.
- huggingface
- bert
- chemical-modelling
- chemical-smiles-data
Sources codes for: Mastering Python for Finance, Second Edition
- machine-learning
- python
- ai
ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission (CHIL 2020 Workshop)
- clinicalbert
- hospital-readmission
- prediction
Full tutorial of computer vision and machine learning basics with OpenCV and Keras in Python.
A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
- feature-selection
- data-science
- python
An OCaml kernel for Jupyter (IPython) notebook
- ocaml
- functional-programming
- jupyter-kernels
- machine-learning
Every day, millions of traders around the world are trying to make money by trading stocks. These days, physical traders are also being replaced by automated trading robots. Algorithmic trading market has experienced significant growth rate and large number of firms are using it. I have tried to build a Deep Q-learning reinforcement agent model to do automated stock trading.
Materials for GWU DNSC 6279 and DNSC 6290.
Usiigaci: stain-free cell tracking in phase contrast microscopy enabled by supervised machine learning
- tensorflow
- python3
- keras
- resnet-101
Wrapper for RDKit's RunReactants to improve stereochemistry handling
ChatGPT Python Applications integrated with third party libraries and modules
⬛ Python Individual Conditional Expectation Plot Toolbox
- machine-learning
- interpretability
Optimising chemical reactions using machine learning
- chemistry
- machine-learning
- optimization
- bayesian-optimization
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
Various Jupyter notebooks about Common Crawl data
- jupyter-notebook
- common-crawl
- aws-athena
- webarchiving
Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications
- cell-annotation
- multiplexed-imaging
- mpif
Various examples of notebooks for working with web archives with the Archives Unleashed Toolkit, and derivatives generated by the Archives Unleashed Toolkit.
- notebooks
- pyspark-notebook
- juypter-notebook
- spark