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Vishal Belsare's Projects

lbann icon lbann

Livermore Big Artificial Neural Network Toolkit

lbimproved icon lbimproved

Dynamic Time Warping (DTW) library implementing lower bounds (LB_Keogh, LB_Improved...)

lcs icon lcs

Extracts Lagrangian Coherent Structures form flow.

lcso icon lcso

Linearly Constrained Separable Optimization

ldps icon ldps

Learning DTW-Preserving Shapelets

ldssf icon ldssf

NIPS 2017 Paper implementation challenge Learning Linear Dynamic Systems via Spectral Filtering

lead-lag icon lead-lag

Estimation of the lead-lag parameter from non-synchronous data.

lean icon lean

Lean Algorithmic Trading Engine by QuantConnect (C#, Python, F#)

leanote icon leanote

Not Just A Notepad! (golang + mongodb) http://leanote.org

learna icon learna

End-to-end RNA Design using deep reinforcement learning

learning-to-learn icon learning-to-learn

Code for "Learning Inductive Biases with Simple Neural Networks" (Feinman & Lake, 2018).

learning_to_beat_the_random_walk icon learning_to_beat_the_random_walk

In this project, I explore various machine learning techniques including Principal Component Analysis (PCA), Support Vector Machines (SVM), Artificial Neural Networks (ANN), and Sentiment Analysis in an effort to predict the directional changes in exchange rates for a list of developed and developing countries.

learnsdd icon learnsdd

Implementation of the Structure Learning Algorithm for Sentential Decision Diagrams

leastfracdiff icon leastfracdiff

Minimal tools for approximating the least fractional difference order that transforms a time series into a stationary one, as suggested by de Prado (2018).

lectures-labs icon lectures-labs

Slides and Jupyter notebooks for the Deep Learning lectures at M2 Data Science Université Paris Saclay

ledger icon ledger

Bengfort household financial analysis tools.

ledger-1 icon ledger-1

Command line double-entry accounting program

ledgersmb icon ledgersmb

Master repository for the LedgerSMB project

leibniz icon leibniz

Leibniz is a python package which provide facilities to express learnable partial differential equations with PyTorch

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