tell me the names of such API's where I can practice my sentiment skills
you can try in tumblr blogs, or webserver analysis.
Related
Are there any concerns with using Snowflake as the data repository for a web API from an enterprise architecture perspective?
I think the question to be asked is how are you going to use the data. It is not clear what you mean by web API data repository. If you are talking about the API interaction data, then Snowflake is not the right choice for that. You should look for a transactional data store for such use cases. However, from that data , if you want to derive insights and analytics you can ingest the transactional data to Snowflake and build your analytics layer on top of it. But the question will be why would you like to do that, most of the API products have that analytics engine already built in their product.
We are trying to design a Knowledge Search box , using Watson Discovery Service . Planning to use Data Crawler to read real-time data from our Knowledge repository. We are looking for some information on how the responses of Discovery services can be ranked .
At this point, you can't affect the ranking of Discovery service results. That feature is on the roadmap, but AFAIK, there's been no announcement date.
Discovery will rank the documents based on relevancy that they have regarding your query. You can use filters with the metadata created to improve the relevancy.
In the latest version of the API relevancy training is an option. With this training you can improve the search results by training the systems with examples based on queries. This will provide a significant uplift in the results.
I am from a Modern retail organisation. Don't have programming knowledge. Can I use your NLP tool to process unstructured text, data and pictures
Please explain what tool are you referring by 'your NLP tool' ?
Google has NLP API that derives insights from unstructured text. You can get details about this API from - https://cloud.google.com/natural-language/
I am using Google API to predict the sentiment of student for professor, I have already trained a model for it. and I also test it. It works.
But I have about 20 K, data in my hand, it is too much to copt and paste to test it. Do you guys have some ideas can make it easy to run for these 20 k data?
thx.
Put your data into a CSV file and upload it to your Google Cloud Storage.
You can upload it via the Google Developers Console, GSUtil or by using Google Cloud Storage API's
The maximum file size for the CSV is 2.5GB, you can find more information on the their developer guide # Training Data File Format
Google Developer Console
Google GSUtil
Cloud Storage API
I am looking for some recommendations on a good data store for activity feeds. The goal is to have a Twitter/Facebook type feed log consisting of various activities users can do throughout our website. The "wall" or "feed" would updated via AJAX showing what the users of the website are currently doing. It will be written to often and then the most recent will be displayed on the site.
(e.g. John Smith recommended Jane Smith's article 2 seconds ago)
We currently are storing the feeds in MySQL but performance has been poor and I'm concerned with hindering performance throughout the rest of the website if we are constantly hitting the database to grab the most recent user activity as well as writing the feeds.
Any recommendations would be greatly appreciated!
Make use of the best caching solutions like memcache to increase performance. Other than scaling, there are no performance-increasing possibilities for an activity feed.
I would vote for using http://redis.io/ or http://www.mongodb.org/ as an alternative to MySQL for short-term, almost live activity feeds across a site. And a cron job to dump history of activities into MySQL for record keeping.
A look at tumblr's or twitters architectures can push you to the right direction as well.
You should take the microservices approach to separate between the datastore that stores the users' actions to the one that store the actual data.
Pub/Sub is the right approach to handle the big stream of users' actions.
Use Kafka or Google Pub/Sub cloud service for a scalable data pipeline. They can take the load with its scalable architecture.
Independently consume the messages from Kafka to some database such as MySQL or Google BigQuery for analytics purposes you must have.