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adanet

Fast and flexible AutoML with learning guarantees.

adasampling

Package for positive unlabeled and label noise learning

adverserial-autoencoder-keras

Keras Implementation of adverserial autoencoder (AAE)

alipy

ALiPy: Active Learning in Python is an active learning python toolbox, which allows users to conveniently evaluate, compare and analyze the performance of active learning methods.

auto_viml

Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

autoencoders_public

Automatic feature engineering using deep learning and Bayesian inference.

autokeras

accessible AutoML for deep learning.

automl

Deep Learning with Metaheuristic

automl-1

Automated Machine Learning Pipeline for tabular data. Designed for predictive maintenance applications, failure identification, failure prediction, condition monitoring, etc.

backtrader-mql5-api

Python Backtrader - Metaquotes MQL5 - API

bitcoin-trader-rl

A profitable cryptocurrency trading environment using deep reinforcement learning and OpenAI's gym

categorical_encoding

R code to encode categorical features for machine learning

cpt

This is the native Python implementation of CPT(compact Prediction Tree)

darch12

Скрипты к статье

darwin-api-tutorials

Tutorial videos, posts, and source code in Python & R to assist algorithmic traders and DARWIN investors in getting up and running with the DARWIN API.

darwinexlabs

Datasets, tools and more from Darwinex Labs - Prop Investing Arm & Quant Team @ Darwinex

deep-trading

Algorithmic trading with deep learning experiments

diaml

Semi-automated machine learning pipelines

differentiable-plasticity

Implementations of the algorithms described in Differentiable plasticity: training plastic networks with gradient descent, a research paper from Uber AI Labs.

dopamine

Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.

dwx-zeromq-connector

Wrapper library for algorithmic trading in Python 3, providing DMA/STP access to Darwinex liquidity via a ZeroMQ-enabled MetaTrader Bridge EA.

easyesn

Library for reservoir computing using echo state networks.

echotorch

A Python toolkit for Reservoir Computing and Echo State Network experimentation based on pyTorch. EchoTorch is the only Python module available to easily create Deep Reservoir Computing models.

elm

Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.

elm_estimator

enas

TensorFlow Code for paper "Efficient Neural Architecture Search via Parameter Sharing"

enas-pytorch

PyTorch implementation of "Efficient Neural Architecture Search via Parameters Sharing"

esnpy

Echo State Networks implementation in Numpy/Scipy

fftrees

An R package to create and visualise fast-and-frugal decision trees (FFTs)

fraud-autoencoder-example

Repository with files used for the blog post "Predicting Fraud with Autoencoders and Keras"