Groups | Search | Server Info | Keyboard shortcuts | Login | Register [http] [https] [nntp] [nntps]
Groups > comp.lang.python > #197281
| Path | csiph.com!fu-berlin.de!uni-berlin.de!not-for-mail |
|---|---|
| From | "info@physalia-courses.org" <info@physalia-courses.org> |
| Newsgroups | comp.lang.python |
| Subject | Machine Learning Methods for Longitudinal Data with Python – Online Course (6-9 May) |
| Date | Fri, 28 Feb 2025 12:56:27 +0100 (CET) |
| Lines | 23 |
| Message-ID | <mailman.121.1740748239.2912.python-list@python.org> (permalink) |
| References | <1740743787.06433745@webmail.jimdo.com> |
| Mime-Version | 1.0 |
| Content-Type | text/plain; charset="UTF-8" |
| Content-Transfer-Encoding | quoted-printable |
| X-Trace | news.uni-berlin.de +eEov0KibTLlu/vCavIs0AJh6m7EuC2OqHsTd6qeaNAQ== |
| Cancel-Lock | sha1:7XtYHCZ+5YV5bnUOKx1YVdmMKJc= sha256:xnFMnHu4z8BEdhg1I2HlYds9pqADSJBAj9gBOti6k58= |
| Return-Path | <info@physalia-courses.org> |
| X-Original-To | python-list@python.org |
| Delivered-To | python-list@mail.python.org |
| Authentication-Results | mail.python.org; dkim=none reason="no signature"; dkim-adsp=none (unprotected policy); dkim-atps=neutral |
| X-Spam-Status | OK 0.039 |
| X-Spam-Evidence | '*H*': 0.93; '*S*': 0.01; 'hands-on': 0.05; 'real- world': 0.07; 'approaches': 0.09; 'exercises,': 0.09; 'graph': 0.09; 'may.': 0.09; 'predictive': 0.09; 'subject:Machine': 0.09; 'url:social': 0.09; 'subject:Python': 0.12; 'received:173': 0.13; '6-9': 0.16; 'bayesian': 0.16; 'combines': 0.16; 'forecasting': 0.16; 'received:173.203': 0.16; 'received:173.203.187': 0.16; 'received:iad3a.emailsrvr.com': 0.16; 'resolution:': 0.16; 'subject:Learning': 0.16; 'time-series': 0.16; 'url- ip:3.255.48.233/32': 0.16; 'url-ip:3.255.48/24': 0.16; 'url- ip:3.255/16': 0.16; 'url-ip:52.215.95.29/32': 0.16; 'url- ip:52.215.95/24': 0.16; 'url-ip:52.215/16': 0.16; 'url- ip:54.194.127.198/32': 0.16; 'url-ip:54.194.127/24': 0.16; 'url- ip:54.194/16': 0.16; 'applications': 0.17; 'to:addr:python-list': 0.20; 'all,': 0.20; 'machine': 0.22; 'register': 0.25; 'cover': 0.26; 'studies': 0.26; 'subject:for': 0.32; 'there': 0.33; 'handling': 0.35; 'mobile:': 0.35; 'networks': 0.35; 'applying': 0.36; 'both': 0.38; 'methods': 0.39; 'still': 0.40; 'data.': 0.40; 'statistical': 0.40; 'learn': 0.40; 'best': 0.61; 'introduction': 0.61; 'dear': 0.62; 'gain': 0.62; 'techniques': 0.62; 'online': 0.63; 'linkedin': 0.64; 'more,': 0.67; 'header:Received:6': 0.67; 'sequence': 0.69; 'subject:Data': 0.71; 'url-ip:18/8': 0.72; 'bias': 0.76; 'subjectcharset:utf-8': 0.80; 'email name:info': 0.80; 'left': 0.83; 'practical': 0.84; 'biases': 0.84; 'carlo': 0.84; 'crucial': 0.84; 'received:(smtp server)': 0.84; 'subject: \xe2\x80\x93 ': 0.84; 'subject:May': 0.84; 'subject:Online': 0.84; 'subject:\xe2\x80\x93': 0.84; 'url:app': 0.86; 'biological': 0.91; 'include:': 0.91; 'url-ip:18.221/16': 0.91; 'from:addr:info': 0.97 |
| X-Auth-ID | info@physalia-courses.org |
| Importance | Normal |
| X-Priority | 3 (Normal) |
| X-Type | html |
| X-Client-IP | 95.91.242.236 |
| X-Mailer | webmail/19.0.28-RC |
| X-Classification-ID | b04fbd3e-5bb6-4227-9ddb-687206f7ac83-1-2 |
| X-Content-Filtered-By | Mailman/MimeDel 2.1.39 |
| X-BeenThere | python-list@python.org |
| X-Mailman-Version | 2.1.39 |
| Precedence | list |
| List-Id | General discussion list for the Python programming language <python-list.python.org> |
| List-Unsubscribe | <https://mail.python.org/mailman/options/python-list>, <mailto:python-list-request@python.org?subject=unsubscribe> |
| List-Archive | <https://mail.python.org/pipermail/python-list/> |
| List-Post | <mailto:python-list@python.org> |
| List-Help | <mailto:python-list-request@python.org?subject=help> |
| List-Subscribe | <https://mail.python.org/mailman/listinfo/python-list>, <mailto:python-list-request@python.org?subject=subscribe> |
| X-Mailman-Original-Message-ID | <1740743787.06433745@webmail.jimdo.com> |
| Xref | csiph.com comp.lang.python:197281 |
Show key headers only | View raw
Dear all, There are still 5 seats left for the upcoming Physalia course "Machine Learning Methods for Longitudinal Data with Python," which is taking place online from 6-9 May. This course will provide a comprehensive introduction to analyzing sequence data (repeated over time or space) when time and causation play a crucial role. This course will cover both classical statistical and modern machine learning approaches to handling time-dependent data. Participants will learn how to recognize and address temporal dependencies, disentangle cause-effect relationships, and apply appropriate modeling techniques for forecasting, survival analysis, and multi-omics data integration. Topics will include: Statistical and machine learning methods for sequence data Bias resolution: confounding, colliding, and mediator biases Time-series forecasting and predictive modeling Bayesian networks and graph models Applications in epidemiology, gene expression, and multi-omics The course combines lectures, hands-on exercises, and case studies to ensure participants gain practical skills for applying these methods to real-world biological data. To register or learn more, please visit [ https://www.physalia-courses.org/courses-workshops/longitudinal-data/ ]( https://www.physalia-courses.org/courses-workshops/longitudinal-data/ ) Best regards, Carlo -------------------- Carlo Pecoraro, Ph.D Physalia-courses DIRECTOR info@physalia-courses.org mobile: +49 17645230846 [ Bluesky ]( https://bsky.app/profile/physaliacourses.bsky.social ) [ Linkedin ]( https://www.linkedin.com/in/physalia-courses-a64418127/ )
Back to comp.lang.python | Previous | Next | Find similar
Machine Learning Methods for Longitudinal Data with Python – Online Course (6-9 May) "info@physalia-courses.org" <info@physalia-courses.org> - 2025-02-28 12:56 +0100
csiph-web