All Videos Tagged Prendki” (Data Science Central) - Data Science Central 2019-11-12T08:26:14Z https://www.datasciencecentral.com/video/video/listTagged?tag=Prendki%E2%80%9D&rss=yes&xn_auth=no DSC Webinar Series: The Essentials of Training Data for Machine Learning tag:www.datasciencecentral.com,2018-09-26:6448529:Video:763549 2018-09-26T22:09:35.844Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-the-essentials-of-training-data-for-machine"><br /> <img alt="Thumbnail" height="135" src="https://storage.ning.com/topology/rest/1.0/file/get/2781544165?profile=original&amp;width=240&amp;height=135" width="240"></img><br /> </a> <br></br>A machine learning algorithm isn’t worth much without great training data to power it. After all, algorithms learn from data, discovering relationships, developing understanding, making decisions, and evaluating their confidence from the training data they’re given. And the better the training data is, the better the model performs. In fact,… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-the-essentials-of-training-data-for-machine"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/2781544165?profile=original&amp;width=240&amp;height=135" width="240" height="135" alt="Thumbnail" /><br /> </a><br />A machine learning algorithm isn’t worth much without great training data to power it. After all, algorithms learn from data, discovering relationships, developing understanding, making decisions, and evaluating their confidence from the training data they’re given. And the better the training data is, the better the model performs. In fact, the quality and quantity of your training data has as much to do with the success of your data project as the algorithms themselves.<br /> <br /> Join us for this latest Data Science Central webinar on the basics of training data where we will cover:<br /> <br /> What training data is and why it’s so important<br /> What training data looks like for a variety of projects<br /> Why training data should be labeled and how to get it labeled<br /> How much training data you need<br /> <br /> Speaker: Jennifer Prendki, VP of Machine Learning -- Figure Eight<br /> <br /> Hosted by: Bill Vorhies, Editorial Director -- Data Science Central