Interactive data analytics

A collection of machine learning examples and tutorials.

Distributed Tensorflow, Keras and PyTorch on Apache Spark/Flink & Ray

Contains all of the queries used within the Complete Guide to Elasticsearch course.

AI deep learning neural network for anomaly detection using Python, Keras and TensorFlow

Python Deep Dive Course - Accompanying Materials

An introduction to machine learning model deployment operations (MLOps) using Python, Docker, Kubernetes and Seldon-Core.

Open source project to deploy Keras Deep Learning models packaged as Docker containers on Kubernetes.

List of tools & datasets for anomaly detection on time-series data.

Anomaly detection related books, papers, videos, and toolboxes

Contains datasets, chapter wise exercises

The Numenta Anomaly Benchmark

A new data structure for accurate on-line accumulation of rank-based statistics such as quantiles and trimmed means

anomaly detection with anomalize and Google Trends data

List of stations and associated metadata

Example Repo for the Udemy Course "Deployment of Machine Learning Models"

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

CDSW Model Operations Demo

Example for end-to-end machine learning on Kubernetes using Kubeflow and Seldon Core

t-Digest data structure in Python. Useful for percentiles and quantiles, including distributed enviroments like PySpark

Excerpt from the Gapminder data, as an R data package and in plain text delimited form

Go client for Kubernetes.