jennyHsiao

ensemble-for-data-stream

Batch incremental ensemble approach

AutoEDASystem

autokeras

accessible AutoML for deep learning.

concept-drift

Algorithms for detecting changes from a data stream.

farewell

mother_in_law

fastai

The fastai deep learning library, plus lessons and and tutorials

git_tutorial

git tutorial

Incremetal_learning_reference

JSAT

Java Statistical Analysis Tool, a Java library for Machine Learning

KitNET-py

KitNET is a lightweight online anomaly detection algorithm, which uses an ensemble of autoencoders.

Kitsune-py

A network intrusion detection system based on incremental statistics (AfterImage) and an ensemble of autoencoders (KitNET)

machine_learning_for_good

Machine learning fundamentals lesson in interactive notebooks

ml-cheatsheet

Machine learning cheatsheet

moa

MOA is an open source framework for Big Data stream mining. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.

models

Models and examples built with TensorFlow

Neural-Net-with-Financial-Time-Series-Data

This solution presents an accessible, non-trivial example of machine learning (Deep learning) with financial time series using TensorFlow

node-facenet

Solve face verification, recognition and clustering problems: A TensorFlow backed FaceNet implementation for Node.js.

pydaal-getting-started

Introduction and tutorials for using PyDAAL, i.e. the Python API of Intel Data Analytics Acceleration Library

pykiteconnect

The official Python client library for the Kite Connect trading APIs

scikit-learn

scikit-learn: machine learning in Python

scikit-multiflow

A multi-output/multi-label and stream data framework. Inspired by MOA and MEKA, following scikit-learn's philosophy.

sklearn-deap

Use evolutionary algorithms instead of gridsearch in scikit-learn

spark-sklearn

Scikit-learn integration package for Spark

SparkDeepMlpGADow30

A Deep Neural-Network based (Deep MLP) Stock Trading System based on Evolutionary (Genetic Algorithm) Optimized Technical Analysis Parameters (using Apache Spark MLlib)

Stock-prediction-Dual-Attention-based-RNN-

Financial time series forecast using dual attention RNN

tpot

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

tsfresh

Automatic extraction of relevant features from time series:

Wavelet-denoising

A script to use the PyWavelet library to perform denoising on a signal using a multi-level signal decomposition using a discrete wavelet transform.

wsae-lstm

implementation of WSAE-LSTM model as defined by Bao, Yue, Rao (2017)

xcessiv

A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.