{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/tflearn-tensorflows-high-level-module-for","title":"TF.Learn: TensorFlow's High-level Module for Distributed Machine Learning","arxiv_id":"1612.04251","date":"2016-12-13","proceeding":null,"authors":["Yuan Tang"],"abstract":"TF.Learn is a high-level Python module for distributed machine learning\ninside TensorFlow. It provides an easy-to-use Scikit-learn style interface to\nsimplify the process of creating, configuring, training, evaluating, and\nexperimenting a machine learning model. TF.Learn integrates a wide range of\nstate-of-art machine learning algorithms built on top of TensorFlow's low level\nAPIs for small to large-scale supervised and unsupervised problems. This module\nfocuses on bringing machine learning to non-specialists using a general-purpose\nhigh-level language as well as researchers who want to implement, benchmark,\nand compare their new methods in a structured environment. Emphasis is put on\nease of use, performance, documentation, and API consistency.","url_abs":"http://arxiv.org/abs/1612.04251v1","url_pdf":"http://arxiv.org/pdf/1612.04251v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"tflearn-tensorflows-high-level-module-for","repo_url":"https://github.com/tensorflow/tensorflow","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"},{"task_slug":"high","task_name":"Vocal Bursts Intensity Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}