Pinned Repositories
ensemble-for-data-stream
Batch incremental ensemble approach
ACM
AutoEDASystem
autokeras
accessible AutoML for deep learning.
concept-drift
Algorithms for detecting changes from a data stream.
docker-elk
The ELK stack powered by Docker and Compose.
docker-stacks
Opinionated stacks of ready-to-run Jupyter applications in Docker.
ebook
classic books of computer science
jennyHsiao's Repositories
jennyHsiao/farewell
mother_in_law
jennyHsiao/wsae-lstm
implementation of WSAE-LSTM model as defined by Bao, Yue, Rao (2017)
jennyHsiao/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.
jennyHsiao/pykiteconnect
The official Python client library for the Kite Connect trading APIs
jennyHsiao/models
Models and examples built with TensorFlow
jennyHsiao/fastai
The fastai deep learning library, plus lessons and and tutorials
jennyHsiao/Stock-prediction-Dual-Attention-based-RNN-
Financial time series forecast using dual attention RNN
jennyHsiao/git_tutorial
git tutorial
jennyHsiao/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
jennyHsiao/ensemble-for-data-stream
Batch incremental ensemble approach
jennyHsiao/machine_learning_for_good
Machine learning fundamentals lesson in interactive notebooks
jennyHsiao/scikit-multiflow
A multi-output/multi-label and stream data framework. Inspired by MOA and MEKA, following scikit-learn's philosophy.
jennyHsiao/Kitsune-py
A network intrusion detection system based on incremental statistics (AfterImage) and an ensemble of autoencoders (KitNET)
jennyHsiao/KitNET-py
KitNET is a lightweight online anomaly detection algorithm, which uses an ensemble of autoencoders.
jennyHsiao/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.
jennyHsiao/concept-drift
Algorithms for detecting changes from a data stream.
jennyHsiao/scikit-learn
scikit-learn: machine learning in Python
jennyHsiao/tsfresh
Automatic extraction of relevant features from time series:
jennyHsiao/autokeras
accessible AutoML for deep learning.
jennyHsiao/tpot
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
jennyHsiao/spark-sklearn
Scikit-learn integration package for Spark
jennyHsiao/Incremetal_learning_reference
jennyHsiao/ml-cheatsheet
Machine learning cheatsheet
jennyHsiao/JSAT
Java Statistical Analysis Tool, a Java library for Machine Learning
jennyHsiao/xcessiv
A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.
jennyHsiao/sklearn-deap
Use evolutionary algorithms instead of gridsearch in scikit-learn
jennyHsiao/AutoEDASystem
jennyHsiao/pydaal-getting-started
Introduction and tutorials for using PyDAAL, i.e. the Python API of Intel Data Analytics Acceleration Library
jennyHsiao/SparkDeepMlpGADow30
A Deep Neural-Network based (Deep MLP) Stock Trading System based on Evolutionary (Genetic Algorithm) Optimized Technical Analysis Parameters (using Apache Spark MLlib)
jennyHsiao/node-facenet
Solve face verification, recognition and clustering problems: A TensorFlow backed FaceNet implementation for Node.js.