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automatic-interpretation-of-otoliths-using-deep-learning

Recent advances in machine learning have brought forth methods that have been remarkably successful in a variety of settings, most notably in image analysis. These methods are now being applied to data analysis in marine sciences, where they have the potential to automate analysis that previously required manual curation. Here we adapt a machine learning model intended for object recognition to the task of estimating age from otolith images. The model is trained and validated on a collection of otolith images from Greenland halibut. We show that the precision of the model's age estimates is comparable to and may even surpass that of human experts. Age reading from otoliths is an important element in the management of many marine stocks, and automating this analysis is an important step to ensure consistency, lower cost, and increase scale.

bidask

Efficient Estimation of Bid-Ask Spreads from Open, High, Low, and Close Prices

bsc_comp_sci_project

final year project teesside

deep-learning-for-regression-of-cod-otoliths

Using the EfficientNet family to predict cod-otolith age.

deep-learning-for-salmon-scales

Fish scales constitute a valuable source of information about individual life histories, but correctly extracting this information requires a highly skilled expert. Here, we train a deep convolutional neural network architecture EfficientNet B4 on a set of about 9000 salmon scale images, and show that it attains good performance on predicting a set of variables used in stock management. Further, we see substantial benefits from user transfer learning with a network pre-trained on ImageNet, even if the salmon scale images are very different from those found in the data used for pre-training.

deepaugment

Discover augmentation strategies tailored for your dataset

demo_marchenko_pastur_analysis

Presentation held at IMR Machine Learning journal club 15. October 2020. Demo Marcenko Pasture distribution applied to eigenvalues of random matrix

dirtyquant

Code that I show on my YouTube Channel

efficientnet

Implementation of EfficientNet model. Keras and TensorFlow Keras.

falkor

Automated Cryptocurrency Trading with PyTorch Models for Stock Price Prediction

freqtrade

Free, open source crypto trading bot

geoext

gxp

High level components for GeoExt based applications.

hashcode2020

library dispatching books - using maximum flow algorithm

hashcode2020_maximum_flow

heapq_with_index

Pop any value of the heap - not just the top element. Convenient feature for scheduling tasks.

hierarchical-sigcwgan

Implementation of the [Hierarchical (Sig-Wasserstein) GAN] algorithm for large dimensional Time Series Generation: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3942764

jib

🏗 Build container images for your Java applications.

journal_club

kaggle

kaggle machine learning projects

leetcode

coding kata

lenet_lekeras

neural network sandbox using Keras

lstm-cnn-charting

Lstm-cnn-charting

machine-learning-for-asset-managers

Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.

machine-learning-for-asset-managers-oslo-bors

miniature

ml_finance_codes

Machine Learning in Finance: From Theory to Practice Book

mlfinlab

MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.

nordnet

Uonfficial wrapper for financial data api from the Scandinavian broker Nordnet

openlayers