A light-weight deep reinforcement learning framework for portfolio management. This project explores the possibility of applying deep reinforcement learning algorithms to stock trading in a highly modular and scalable framework.
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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.
ZeroCostDL4Mic: A Google Colab based no-cost toolbox to explore Deep-Learning in Microscopy
🍇 GRAPE is a Rust/Python Graph Representation Learning library for Predictions and Evaluations
- graph
- high-performance
- machine-learning
- knowledge-graph
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
Solve captcha without manually labeling a training set
- keras
- gan
- neural-network
- generative-adversarial-network
A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
- feature-selection
- data-science
- python
Reference mapping for single-cell genomics
- single-cell
- deep-learning
- rna-seq-analysis
- data-integration
The fast Continuous Wavelet Transform (fCWT) is a library for fast calculation of CWT.
- cwt
- matlab
- cpp
- optimization
Genomic Pretrained Network - GPN, GPN-MSA, PhyloGPN, GPN-Star
- dna
- language-model
- variant-effect-prediction
- genomics
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
TranslatedLLM teaching material for high school students: based on Karpathy's microgpt, for Google Colab
Pan-Cancer Integrative Histology-Genomic Analysis via Multimodal Deep Learning - Cancer Cell
- histology
- wsi-images
- pan-cancer-analysis
- genomics
Usiigaci: stain-free cell tracking in phase contrast microscopy enabled by supervised machine learning
- tensorflow
- python3
- keras
- resnet-101
scPerturb: A resource and a python/R tool for single-cell perturbation data
- cite-seq
- database
- perturbation
- scatac-seq
Repository for Nicheformer: a foundation model for single-cell and spatial omics
🏃 The go-to single-cell Foundation Model
- batch-correction
- cell-biology
- celltype-annotation
- denoising
Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.
- disentanglement
- drug-discovery
- genomics
- perturbation
⬛ Python Individual Conditional Expectation Plot Toolbox
- machine-learning
- interpretability
Optimising chemical reactions using machine learning
- chemistry
- machine-learning
- optimization
- bayesian-optimization
InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
- probabilistic-programming
- neural-network
- tensorflow
- keras-tensorflow
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