Katz - Time Series Analysis Framework

Tue, 22 Jun 2021 10:00:00 +0200

Time series analysis is a fundamental domain in data science and machine learning, with massive applications in various sectors such as e-commerce, finance, capacity planning, supply chain management, medicine, weather, energy, astronomy, and many others.

Time Series Analysis

Time series analysis as a statistical technique is used to examine and model time-dependent data. Some common features of time series analysis tools include:

Time series decomposition: the ability to break down a time series into its component parts, such as trend, seasonality, and residuals
Forecasting: the ability to predict future values of a time series based on past data
Anomaly detection: the ability to identify unusual or unexpected behavior in a time series
Multivariate analysis: the ability to analyze multiple time series simultaneously, taking into account the relationships between them
Feature extraction/embedding: the ability to extract meaningful features from time series data or to represent time series data in a lower-dimensional space for further analysis.

These are just a few examples of the types of functionality that may be included in a time series analysis tool. Let’s see what Kats can provide us with.

Megvii Open Sources Deep Learning Framework

Sat, 28 Mar 2020 00:15:00 +0100

Chinese Artificial Intelligence (AI) start-up Megvii Technology Limited announced that it makes its deep learning framework open-source, as China steps up the development of home-grown AI and makes the technologies more accessible to reduce reliance on US platforms.

Framework on Den's Hub: Technology Solutions, Guides and Best Practices

Katz - Time Series Analysis Framework

Time Series Analysis

Megvii Open Sources Deep Learning Framework