18 Matching Annotations
  1. Oct 2024
  2. Feb 2023
  3. May 2022
  4. Apr 2022
  5. Feb 2022
    1. source - https://www.youtube.com/watch?v=dPb1bg1mVLg

      Intro: * Project-based approach * Core fundamentals * Not a tutorial

      See the companion modules in the link: https://www.engineeringwithutsav.com/roadmaps

      ...also recommendations for: * Data structure and algo books * Building good coding habits * Free resources

  6. Jun 2021
  7. May 2021
  8. Feb 2021
  9. Nov 2020
  10. Oct 2020
    1. We first discuss exam-ples of this model and then formulate a critique of it. Based on this discussion, we introdu

      Here the authors tell us the structure of the article - presentation of evidence and then a critique of this evidence - adding their perspectives.

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  11. Aug 2020
    1. Online courses tend to be based around linear playlists of videos, along with associated readings and other activities. These often look like university courses filmed and translated more or less directly to online form. More internet native courses tend to be shorter and more focused, but still just as linear and video-centric.

      agree with this.

      I've often thought that at times learning feels more like the Path fo Exile skill spider-web than a linear path.

      Many 'road maps', 'how to' feels like a ladder - and then it's not always clear how much you need to learn about a certain step before moving onto the next step, while also failing to realize that you may have learned the outcomes from the step in another way.

  12. Mar 2019
    1. The main purpose of the Discovery IN is to provide interfaces and other user-facing services for data discovery across disciplines. We explore new and innovative ways of enabling discovery, including visualizations, recommender systems, semantics, content mining, annotation, and responsible metrics. We apply user involvement and participatory design to increase usability and usefulness of the solutions. We go beyond academia, involving users from all stakeholders of research data. We create FAIR and open infrastructures, following the FAIR principles complemented by the principles of open source, open data, and open content, thus enabling reuse of interfaces and user-facing services and continued innovation. Our main objectives are:
  13. Aug 2018
    1. In the rest of this chapter, we describe the development of the academicliterature on peer production and collective intelligence in three areas – or-ganization, motivation, and quality. In each area, we introducefoundationalworkconsisting primarily of earlier scholarship that sought to describe peerproduction and establish its legitimacy. Subsequently, we characterize work,usually more recent, that seeks to pursuenew directionsand to derive morenuanced analytical insights. Because FLOSS and Wikipedia have generatedthe majority of the peer production research to date, we focus on researchanalyzing those efforts. For each theoretical area, we briefly synthesize bothfoundational work and new directions and describe some of the challenges forfuture scholarship. Neither our themes nor our periodization are intended toencompass the complete literature on peer production. Instead, they reflectcore areas of research that speak most directly to the literature on collectiveintelligence and locate peer production within that broader phenomenon. Weconclude with a discussion of several issues that traverse our themes and impli-cations of peer production scholarship for research on collective intelligencemore broadly.

      Nice example of foregrounding and roadmapping for an essay/paper

  14. Aug 2013
    1. Flash messages (#233) Static asset build script (#161) Finish registration form flow (#159) Separate detail and bucket views (#162)

      the road map on hypothes.is