vishalbelsare Goto Github PK

ad-1

Fast, transparent calculations of first and second-order automatic differentiation

ad-blocking

Prototypes of ad blocking techniques proposed in the "Future of Ad Blocking" paper

adaboost

Adaboost-Reg and RBF-Network code

adaboost-trading-system

An trading system basing on adaboost algorithm using weak classifiers assembled to predict.

adabound

An optimizer that trains as fast as Adam and as good as SGD.

adahessian

ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning

adanet

Fast and flexible AutoML with learning guarantees.

adapted-gspan

adaptive-regularization

Hyperparameter-free weight decay implemented in TensorFlow.

adaptivegp

Fully nonstationary, heteroscedastic GP for Matlab

adatime

Official implementation of AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data

ade

Asynchronous Differential Evolution, with efficient multiprocessing

adenine

ADENINE: A Data ExploratioN PipelINE

adept

Fast automatic differentiation library in C++

adept-2

Combined array and automatic differentiation library in C++

adjsim

An Agent Based Modelling Engine tailored for Reinforcement Learning.

adjusted-cross-entropy-loss-function

Adjusted CrossEntropy loss function that integrates the distance between the true class and the predicted one

adjusted-mae-loss-function

Adjusted MAE loss function is a custom loss function for Pytorch that integrates a penalty for the difference in sign between the true y and the predicted y.

adlib

Game-Theoretic Adversarial Machine Learning Library

admm

Solving Statistical Optimization Problems Using the ADMM Algorithm

admm-1

Algorithms using Alternating Direction Method of Multipliers

adv-alstm

Code for paper "Enhancing Stock Movement Prediction with Adversarial Training" IJCAI 2019

adv-financial-ml-marcos-exercises

Exercises of the book: Advances in Financial Machine Learning by Marcos Lopez de Prado

adv_fin_ml_exercises

Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]

advanced-deep-trading

Mostly experiments based on "Advances in financial machine learning" book

advances-in-financial-machine-learning

Codes and Solutions for Advances in Financial Machine Learning by Marcos Lopez de Prado

adversarial-robustness-toolbox

This is a library dedicated to adversarial machine learning. Its purpose is to allow rapid crafting and analysis of attacks and defense methods for machine learning models. The Adversarial Robustness Toolbox provides an implementation for many state-of-the-art methods for attacking and defending classifiers. https://developer.ibm.com/code/open/projects/adversarial-robustness-toolbox/

advisor

Open-source implementation of Google Vizier for hyper parameters tuning

ae_ts

Auto encoder for time series

aesara

Aesara is a Python library that allows one to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.