Lucidworks builds AI-powered search and discovery applications for some of the world's largest brands. Fusion, Lucidworks' advanced development platform, provides the enterprise-grade capabilities needed to design, develop and deploy intelligent search apps at any scale. Reddit, Red Hat, Moody’s, Commvault, and the US Census are just of few of the companies that rely on Lucidworks every day to power their consumer-facing and enterprise search apps. Lucidworks’ investors include Top Tier Capital Partners, Shasta Ventures, Granite Ventures, Silver Lake Waterman, and Walden International.
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You have passed the vibe check bruh
Thanks for sharing this. It's very insightful and detailed.
Did this woman just have a bad breakup before doing this presentation? She sounds like she's having a mental breakdown
Really insightful and well explained 🎉 Learned a lot from this video
where do you put thekubectl logs-f <pod name>? in graphana?
Thanks for this insightful talk
If there's no target variable that we're searching for with clustering, how do we know that a certain clusters will have a higher likelihood of spending more? Does it require more modeling after we've found these clusters?
We can take the mode / mean / median of different attributes within the cluster to "group" different data points together based on that
Problems are easy to find. What are the solutions?
nerd
dude, you are a life saver! subscribed!
This is probably the best explanation i have seen out there. but I would have liked to see some hands on as well to fully showcase the setup.
This video on natural language search with knowledge graphs is really interesting! It's amazing how much more intuitive and efficient it can be to search for information when you can just ask a question in plain language, rather than trying to come up with a bunch of specific keywords. One tool that I've found to be really helpful for natural language search is the ExpertRec Custom Site Search plugin. It uses knowledge graphs to understand the context of my queries, so I can get more accurate and relevant results. Plus, it's super easy to use and can be customized to fit the needs of any website. Highly recommend giving it a try if you're looking to streamline your search process
Omg I NEED thissss. Thank you so much!
Thx dude
Have you guys migrated to solr9 already? Having issues mimicking the same auto scaling functionality in solr8. Thanks!
MERRY CHRISTMAS 🎄 love you all so much, hope you’re having a wonderful holiday ❤🎅🏻
Thank you for sharing, super interesting study and awesome presentation. Thanks for the valuable feedback!
Excellent presentation 👏 👌 👍
Good job man, keep it up!
very nice
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😜 𝐩𝓻Ỗ𝓂Ø𝓈Ｍ
How can I get a hold of these slides
Thanks for sharing this comprehensive insights! Keep up with great contents 🙌
𝓅𝓇o𝓂o𝓈𝓂
amazing as always thanks simon
Awesome work. Thank you!
great presentation , the more i think about it, the more SKG sounds like word2vec , take average of word embedding for Java and Scala and find word embedding(s) that are close to it. Then if context make a difference use embedding generated by language models, this way we can differentiate between BBQ in 2 different contexts as well.
Great presentation, but that weird auto-panning of the camera is SUPER distracting. I had to put a Post-It note over your image...sorry Erick!
I watched your video, it was great to see the video, a lot of nice content but I noticed that there are not enough views to subscribe to like comments. If you want, you will get many like and comment views on your video through advertisements. This will help to rank your video. And it will be very professional we can talk about how to grow...
code?
Wonderful description of brain hemispheres.
how to get other collections fields ? Example , customers collection has customer_name, customer_id, orders has orderid,customer_id,total_amount, firing up query on orders collection with cross join on customers collection , I want result like orderid,customer_id,customer_name,total_amount in other words in RDBMS we do left join to pull columns from other table, how to achieve this?
Solr joins are only for filtering data, they do not offer more fields to return. I think if you need those extra fields then you need to look them up in the application layer, or denormalize it at indexing time.
Whats the difference between Ranking and Sorting? If we are using a formulae e.g. 2 * featureA + 4.5 * featureB to generate the score, then we can use this formulae with traditional programming also and sort the results, why do we need ML here?
To figure out what 2 and 4.5 should br
Any idea in 4.x to 5.x migration?
Excellent Video. Thanks. Can we add Relevancy(Applying Scores and Boosting) in Streaming Queries.
Great presentation with useful examples. Thanks Trey.
Any idea in 4.x to 5.x migration?
Great demo. Thank you Josh!
Error - ‘skip’ is unknown (not mapped to a valid tuplestream) can we get more information that how to use skip and limit.
Personalization.ai
Are semantic search and intent search and Nlp search the same things ?
recommendations.ai
Great presentation. Good work there. 👍🏽
linguist.ai
Excellent presentation. Can you please explain why zookeeper was hosted as different services and how route 53 was used. Is it possible to share repo that contains ECS Service and Task definition
Hiii
LTR Steps: 8:29 Collecting training data: 10:16 Model evaluation: 18:41 Feature latency: 22:03 Index static features: 24:05 Changing to docvalues: 25:06 Grouping: 29:00 Rolling out: 33:00 Takeaways: 35:00
Whats the difference between Ranking and Sorting? If we are using a formulae e.g. 2 * featureA + 4.5 * featureB to generate the score, then we can use this formulae with traditional programming also and sort the results, why do we need ML here?
@@deepakkumarjoshi The model figures out the exact weights for each feature. Based on those features the most relevant documents according to BM25 are re-ranked and then returned to the user
Awesome content. Thanks!
Can we tag the incoming query? If yes then how to do that with SOLR?