kaggle-environments VS CouchDB

If you are interested in Data Science, you may want to look at Kaggle competitions. https://www.kaggle.com/competitions

Secondly, if you feel like you do not have enough skills or a lack of practice answering problem statements, there are a lot of good websites where you can find interesting projects. I would recommend starting participating in some Kaggle competitions or download some free Google datasets and start playing with them.

For reference: Kaggle is a Google product. You can see the list of current competitions here.

You could try Kaggle competitions, or participating in forecasting markets (as you stated) is another option. You don't need any specific skill set to be a forecaster, the rules of the bet are stipulated and from there it's just based on your ability to predict the outcome. You could also try your hand at investing in the stock market, or try and make money betting on sports games. If you're very good at this stuff I'm sure you can make a lot of money doing it. The thing to keep in mind is that generally video games are much much easier than real life

As to the specifics of your projects, that's up to you. Try browsing Kaggle; check out some of the work we have on The Pudding; check out some journalism examples to see what you can try to build on or improve.

You might want to look at kaggle competitions.

CouchDB is a json based database for simple projects. The fork pouchdb offers lots of support for offline.

Apache CouchDB belongs to the family of NoSQL databases. It is a document store with a strong focus on replication and reliability. One of the most significant differences between CouchDB and a relational database (besides the absence of tables and schemas) is how you query data. Relational databases allow their users to execute arbitrary and dynamic queries via SQL. Each SQL query may look completely different than the previous one. These dynamic aspects are significant for use cases where you work exploratively with your dataset but don't matter as much in a web context. Additionally, defining an index for a specific table is optional. Most developers will define indices to boost performance, but the database does not require it.

I just turns out you can't always do that in a real codebase. For example see here:

  https://github.com/apache/couchdb/blob/23efd8e5b1aa96ef01640fec03a5fedc945ba8b9/src/couch_mrview/src/couch_mrview_http.erl#L228

Example: Apache Cassandra, CouchDB.

For non-SQL-based databases, consider MongoDB, or CouchDB, which are very easy to get started with.

The Apache CouchDB server. It stores Annotation data.

CouchDB

You can implement the sync algorithm from scratch, or you can use tools like CouchDB and turtleDB to help you.