How do you use feedback and data to improve your Machine Learning presentations?

1 Know your audience

Before you design your presentation, you need to understand who you are talking to and what they expect from you. Are they technical or non-technical? Are they familiar with ML or not? Are they interested in the details or the big picture? What are their goals and pain points? You can use surveys, interviews, or online research to gather feedback and data about your audience. This will help you tailor your content, language, and visuals to their needs and preferences.

3 Simplify your message

One of the most common challenges of ML presentations is to simplify complex and technical concepts without losing accuracy or clarity. You should avoid using jargon, acronyms, or equations that may confuse or bore your audience. Instead, you should use simple and clear language, analogies, examples, and stories to explain your ML concepts. You should also focus on the key points and benefits of your ML solution, rather than the details and features. You can use feedback and data to test your message and see if your audience understands and remembers it. For example, you can use quizzes, polls, or Q&A sessions to check their comprehension and recall.

4 Visualize your data

Another important aspect of ML presentations is to visualize your data in a way that is informative, attractive, and persuasive. You should use charts, graphs, diagrams, or images that show your data clearly and highlight your main findings or recommendations. You should also use colors, fonts, and layouts that are consistent, readable, and appealing. You can use feedback and data to improve your data visualization and see if it captures and holds your audience's attention. For example, you can use eye-tracking, heat maps, or click-through rates to measure how your audience interacts with your visuals.

5 Practice and refine

Finally, you should practice and refine your ML presentation before you deliver it to your audience. You should rehearse your presentation several times, preferably in front of a test audience that can give you honest and constructive feedback. You should also record yourself and watch your presentation to identify and fix any issues with your content, delivery, or design. You can use feedback and data to polish your presentation and make it more engaging and effective. For example, you can use timers, scores, or comments to assess your performance and improve your timing, tone, or transitions.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?