Tensorflow implementation of "Learning Deep Features for Discriminative Localization"
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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.
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
Open source remote sensing dataset with benchmarks
Materials for GWU DNSC 6279 and DNSC 6290.
This trading-gym is the first trading for agent to train with episode of short term trading itself.
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
ChatGPT Python Applications integrated with third party libraries and modules
Analysis of High Frequency Trading on Bitcoin exchanges
This repository contains notebooks that show the usage of TensorFlow Lite for quantizing deep neural networks.
- tensorflow-2
- tensorflow-lite
- on-device-ml
- model-quantization
A python Two Source Energy Balance model for estimation of evapotranspiration with remote sensing data
- source-energy-balance
- canopy
- soil
- radiometric-temperatures
An interactive Quiz generator for Jupyter notebooks and Jupyter Book
- quiz
- jupyter-notebook
- jupyter-notebooks
- interactive
Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.
- disentanglement
- drug-discovery
- genomics
- perturbation
Optimising chemical reactions using machine learning
- chemistry
- machine-learning
- optimization
- bayesian-optimization
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
This project aims to classify human activities using data obtained from accelerometer and gyroscope sensors from phone and watch.
A TensorFlow implementation of the Mnemonic Descent Method.
- tensorflow
- menpo
- face
- face-alignment
Detecting cancers on mobile phones
PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturbations at bulk and single-cell levels.
Big Data essentials: Hadoop, MapReduce, Spark. Explore tutorials and demos in Jupyter notebooks—most are self-contained and live, ready to run with a click.
BulkFormer: A large-scale foundation model for human bulk transcriptomes
a nose plugin for finding and running IPython notebooks as nose tests