Hierarchical Forecasting in Python | Nixtla
ABOUT THE TALK:
A vast amount of time series datasets are organized into structures with different levels or hierarchies of aggregation.
In this talk, we introduce the open-source Hierarchical Forecast library, which contains different reconciliation algorithms, preprocessed datasets, evaluation metrics, and a compiled set of statistical baseline models. This Python-based framework aims to bridge the gap between statistical modeling and Machine Learning in the time series field.
ABOUT THE SPEAKER:
Max Mergenthaler is the CEO and Co-Founder of Nixtla, a time-series research and deployment startup. He is also a seasoned entrepreneur with a proven track record as the founder of multiple technology startups. With a decade of experience in the ML industry, he has extensive expertise in building and leading international data teams. Max has also made notable contributions to the Data Science field through his co-authorship of papers on forecasting algorithms and decision theory.
ABOUT DATA COUNCIL:
Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.
Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.
FOLLOW DATA COUNCIL:
Twitter: https://twitter.com/DataCouncilAI
LinkedIn: https://www.linkedin.com/company/datacouncil-ai/
Видео Hierarchical Forecasting in Python | Nixtla канала Data Council
A vast amount of time series datasets are organized into structures with different levels or hierarchies of aggregation.
In this talk, we introduce the open-source Hierarchical Forecast library, which contains different reconciliation algorithms, preprocessed datasets, evaluation metrics, and a compiled set of statistical baseline models. This Python-based framework aims to bridge the gap between statistical modeling and Machine Learning in the time series field.
ABOUT THE SPEAKER:
Max Mergenthaler is the CEO and Co-Founder of Nixtla, a time-series research and deployment startup. He is also a seasoned entrepreneur with a proven track record as the founder of multiple technology startups. With a decade of experience in the ML industry, he has extensive expertise in building and leading international data teams. Max has also made notable contributions to the Data Science field through his co-authorship of papers on forecasting algorithms and decision theory.
ABOUT DATA COUNCIL:
Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.
Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.
FOLLOW DATA COUNCIL:
Twitter: https://twitter.com/DataCouncilAI
LinkedIn: https://www.linkedin.com/company/datacouncil-ai/
Видео Hierarchical Forecasting in Python | Nixtla канала Data Council
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
Hot or Not: Latest Trends & Buzzwords in DataThe Road to Exceptional Data CorrectnessHow to End the Long tail of Most Data Requests | NarratorWhat I Don't Want to Exist in the Data World in 5 Years | Seattle Data GuyData Contracts in the Modern Data Stack | WhatnotIncident Management for Data People | BigeyeAutomatically Fix Data Issues & Label Errors in Most ML Datasets | CleanlabContinuous Data Pipeline for Real time Benchmarking & Data Set Augmentation | TeleskopeData Product Success: Aligning with Data's Core Purpose | EnteraData Products Aren't Just for Data Teams! LightdashInnovating on Software Development | Fast AIThe Story of DevRel at Snowflake - How We Got Here | SnowflakeAI The Future is NowHow to Be a 10x Analyst | HyperqueryWhat it Takes to Support the World's Most Popular Open Source Communities | NumFOCUSHow Vercel Builds Dozens of Metrics from One Heterogenous TableGenerative AI for Search | TonitaFrom 1 to IPO: Growing the Data Team and Data Culture at GitLabWhen to Move from Batch to Streaming and how to do it without hiring an entirely new team | BytewaxDesigning & Building Metric Trees