Before Memmo my notes were scattered across PDFs. Now a workspace pulls everything into one place — I see exactly what's still left to study.
Interactive visualization and visual analytics tools have been designed and developed in the past and will be developed in the future as well. In each application domain in which data is measured, generated, and recorded we see a potential candidate for an interactive visualization tool with the goal to find insights and knowledge in the data. This knowledge can be found either visually by humans’ interventions or algorithmically by the machine, in the best case by applying both concepts in combination as in visual analytics. One of the easiest ways to get an interactive visualization tool running is by means of dashboards, typically implemented as webpages that can run in a web browser and are accessible online, creating some kind of web-based solution.
This book describes ways to design and implement dashboards based on the programming language Python, the graphics library Plotly, and Dash. The readers can use the provided dashboard codes as a starting point and extend the functionality and features on their desire.
Technical topics discussed in the book include:
Before Memmo my notes were scattered across PDFs. Now a workspace pulls everything into one place — I see exactly what's still left to study.
Memmo's summaries are gold before exams. I don't have to re-read 800 pages two weeks before — just the important parts.
The AI chat has saved me the night before an exam more than once. I just keep asking until I get it — no waiting on a study group to reply.
The quizzes hit exactly what I need to know. Memmo tracks what I get stuck on — so I only practice what's worth it.
Flashcards with spaced repetition are magic. Memmo knows when I'm about to forget something and brings it back.
The AI podcasts are my favorite. I listen on my way to school and get a recap without sitting at a computer.
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