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WebClinic's Projects

kabu_beta icon kabu_beta

張が独自開発した株情報取得ツールです

kadalu icon kadalu

A lightweight Persistent storage solution for Kubernetes / OpenShift / Nomad using GlusterFS in background.

kafka-http-pusher icon kafka-http-pusher

auto-balanced consumer which will fetch message from kafka and push forward through http POST.

kafka-ml icon kafka-ml

Kafka-ML: connecting the data stream with ML/AI frameworks (now TensorFlow and PyTorch!)

kafka_stock icon kafka_stock

A financial data processing and visualization platform using Apache Kafka, Apache Cassandra, and Bokeh.

kafkasaga icon kafkasaga

Simple microservice that uses Kafka + Saga Pattern to provide complicated message processing logic using simple actions.

kairos icon kairos

Kairos aims to help you save time by automating repetitive tasks on TradingView such as scanning markets for setups, and refreshing alerts as well as creating new ones.

kalman-and-bayesian-filters-in-python icon kalman-and-bayesian-filters-in-python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

kaneda icon kaneda

Configurable Python library for metrics collection

kara-trader icon kara-trader

Uses a recurrent neural network to automatically make stock market trades through Alpaca

karoo_gp icon karoo_gp

A Genetic Programming platform for Python with TensorFlow for wicked-fast CPU and GPU support.

katana icon katana

Katana project is a FastAPI template for ASAP 🚀 ML API deployment

kati icon kati

The Kraken Automated Trading Interface (KATI) is a python program I have developed to use analysis from the Technical Analysis API and the Kraken Trading API to automatically determine buying and selling of cryptocurrency.

kats icon kats

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.

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