Ambientflix
Unmute
Mentor: Ed Bukoski, Engineer at Netflix
Team members: Allen Lin, Jessica De Mota Munoz, Emily Hugan, Nguyen Pham, Andrea Arce Gutierrez, Kimberly Yu
Create movie and TV show recommendations based on signals from your ambient environment. Imagine visiting Netflix and seeing a recommendation row based on your local weather, current geographical location, local news, or the past hour of your personal Twitter feed!
We will divide up into two teams. One team will source data from weather services, Twitter API, news feeds, or any other source that has data from the local environment. The second team will use these as input to query movie data from themoviedb.org and form a list of movie and TV show recommendations (bonus for links to streaming services where this content is hosted). We will figure out the final presentation format as we go, it could be a command line, REST (JSON) API, or a web site.
Team members: Allen Lin, Jessica De Mota Munoz, Emily Hugan, Nguyen Pham, Andrea Arce Gutierrez, Kimberly Yu
Create movie and TV show recommendations based on signals from your ambient environment. Imagine visiting Netflix and seeing a recommendation row based on your local weather, current geographical location, local news, or the past hour of your personal Twitter feed!
We will divide up into two teams. One team will source data from weather services, Twitter API, news feeds, or any other source that has data from the local environment. The second team will use these as input to query movie data from themoviedb.org and form a list of movie and TV show recommendations (bonus for links to streaming services where this content is hosted). We will figure out the final presentation format as we go, it could be a command line, REST (JSON) API, or a web site.
How much experience does your group have? Does the project use anything (art, music, starter kits) you didn't create?
CodeDay Labs advanced-track team
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