# From Impact Reports to Drought Prediction: A Machine Learning approach

**URL:** <https://forum.access-hive.org.au/t/from-impact-reports-to-drought-prediction-a-machine-learning-approach/1203>\
**Category:** Main Program Day 2\
**Tags:** machine-learning, video, talk, session-5\
**Created:** [31 August 2023 07:24 UTC](https://forum.access-hive.org.au/t/from-impact-reports-to-drought-prediction-a-machine-learning-approach/1203 "2023-08-31T07:24:39Z")\
**Posts on this page:** 4\
**Page:** 1

<div class="post-metadata">

**Author:** ![Sanaa](https://sea2.discourse-cdn.com/flex020/user_avatar/forum.access-hive.org.au/sanaa/32/2354_2.png) [@Sanaa](https://forum.access-hive.org.au/u/Sanaa)\
**Post date:** [31 August 2023 07:24 UTC](https://forum.access-hive.org.au/t/from-impact-reports-to-drought-prediction-a-machine-learning-approach/1203/1 "2023-08-31T07:24:39Z")

</div>

# Title

_From Impact Reports to Drought Prediction: A Machine Learning approach_

# Speaker

Sanaa Hobeichi (@Sanaa), UNSW

# Recording

[![](https://us1.discourse-cdn.com/flex020/uploads/access1/original/2X/1/10465f231db74fcbb5336bc7943e7a6b7fa70c70.jpeg "Sanaa Hobeichi UNSW") ](https://www.youtube.com/watch?v=ZYkxU3geJDQ)

# Location

Weston Theatre (and online). See the [main workshop help topic for zoom details](https://forum.access-hive.org.au/t/workshop-information-everything-you-need-to-know/1172#zoom-details-3).

# Time

9:30-9:45 am

# Abstract

# Feedback

If you want to ask questions of the speaker **you must reply to this topic**. We encourage all speakers and attendees to continue fruitful discussions in replies to this topic for as long as they wish (weeks, years ..). This topic will remain available for as long as this site exists.

**Note:** This topic is part of the [2023 ACCESS Community Workshop](https://forum.access-hive.org.au/c/access-workshop-2023/61) main session

---

<div class="post-metadata">

**Author:** ![system](https://us1.discourse-cdn.com/flex020/uploads/access1/original/1X/d8217396f46876e65685c86067b9f8c89d230627.png) [@system](https://forum.access-hive.org.au/u/system)\
**Post date:** [5 September 2023 23:25 UTC](https://forum.access-hive.org.au/t/from-impact-reports-to-drought-prediction-a-machine-learning-approach/1203/2 "2023-09-05T23:25:27Z")

</div>



---

<div class="post-metadata">

**Author:** ![AndyHoggANU](https://sea2.discourse-cdn.com/flex020/user_avatar/forum.access-hive.org.au/andyhogganu/32/43_2.png) [@AndyHoggANU](https://forum.access-hive.org.au/u/AndyHoggANU)\
**Post date:** [6 September 2023 00:06 UTC](https://forum.access-hive.org.au/t/from-impact-reports-to-drought-prediction-a-machine-learning-approach/1203/3 "2023-09-06T00:06:14Z")

</div>

Hi @Sanaa - nice talk. I’m wondering if you’ve tried evaluating the skill of your method in comparison to any of the other seasonal forecasts available?

---

<div class="post-metadata">

**Author:** ![Sanaa](https://sea2.discourse-cdn.com/flex020/user_avatar/forum.access-hive.org.au/sanaa/32/2354_2.png) [@Sanaa](https://forum.access-hive.org.au/u/Sanaa)\
**Post date:** [6 September 2023 01:25 UTC](https://forum.access-hive.org.au/t/from-impact-reports-to-drought-prediction-a-machine-learning-approach/1203/4 "2023-09-06T01:25:14Z")

</div>

Hi Andy, no I haven’t. But thank you for the idea. I like it
