The Past, Present, and Future of Automated Machine Learning | SciPy 2018 | Randal Olson
Automated Machine Learning (AutoML) has been described as a "quiet revolution in AI" that is poised to dramatically change the data science landscape by using AI to automate many of the time-consuming aspects of applying Machine Learning to real-world problems. Academic researchers, startups, and tech giants alike have begun developing AutoML methods and tools ranging from simple open source prototypes to industry-scale software products. Yet beyond all the hype and vague tech jargon, many are left wondering: What is AutoML, really? In this talk, I will draw from my AutoML research experience to discuss the benefits of AutoML and highlight some promising future directions of the field, including Python packages and other existing tools that offer AutoML solutions.
See the full SciPy 2018 playlist at https://www.youtube.com/playlist?list=PLYx7XA2nY5Gd-tNhm79CNMe_qvi35PgUR
Видео The Past, Present, and Future of Automated Machine Learning | SciPy 2018 | Randal Olson канала Enthought
See the full SciPy 2018 playlist at https://www.youtube.com/playlist?list=PLYx7XA2nY5Gd-tNhm79CNMe_qvi35PgUR
Видео The Past, Present, and Future of Automated Machine Learning | SciPy 2018 | Randal Olson канала Enthought
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
Intro to AutoML + Hands-on Lab - Erin LeDell, Machine Learning Scientist, H2O.aiWhat is automated machine learning? | KaggleGetting Started with TensorFlow and Deep Learning | SciPy 2018 Tutorial | Josh GordonAround the World in 80 Ways: An Introduction to Working w/ Geodata & Cartopy | SciPy 2018 TutorialFrank Hutter and Joaquin Vanschoren: Automatic Machine Learning (NeurIPS 2018 Tutorial)Yuriy Guts, DataRobot. Automated Machine LearningHyperopt: A Python library for optimizing machine learning algorithms; SciPy 2013Automation of AI Design | Marius Lindauer | TEDxFreiburgAutoML Vision - Part 1AutoML - Paco Nathan | PyData Hamburg May 2021Automatic Machine Learning - Prof. Frank HutterA Deepdive into AutoML Tables | Tin-Yun Ho & Da Huang | Kaggle DaysUsing Google AutoML NLP (Natural Language Processing)Bayesian Data Science Two Ways: Simulation and Probabilistic Programming | SciPy 2018 TutorialInterpretable Machine Learning Using LIME Framework - Kasia Kulma (PhD), Data Scientist, Aviva[GCP專門家] AutoML 線上研討會 - 擁有專屬自己的機器學習模型Unsupervised Learning | Clustering and Association Algorithms in Machine Learning | @edureka!"Machine Learning for Partial Differential Equations" by Michael BrennerAutomated Machine Learning In Python (Automl)