This presentation was given by our Lead Data Scientist, Adauto Braz, at Papis.io/latam-2019 sharing some insights about our clustering project using unsupervised learning algorithms such as DBSCAN, K-Means.
Scratch Workshop at Riverside School, Ahmedabad - By GSC DAIICTShreyans Gandhi
This is the presentation made by me at the Scratch Software Workshop conducted at the Riverside School, Ahmedabad.
The aim of the workshop was to get the grade 7 students know what amazing they can do with Scratch Software.
Video and slides synchronized, mp3 and slide download available at URL https://bit.ly/2SXXXiD.
Katharina Probst talks about what it means to act like an owner and why teams need ownership to be high-performing. When team members, regardless of whether they have a formal leadership role or not, act like owners, magical things can happen. She shares ideas that we can apply to our own work, and talks about how to recognize when we don’t live up to our own expectations of acting like an owner. Filmed at qconsf.com.
Katharina Probst is a Senior Engineering Leader, Kubernetes & SaaS at Google. Before this, she was leading engineering teams at Netflix, being responsible for the Netflix API, which helps bring Netflix streaming to millions of people around the world. Prior to joining Netflix, she was in the cloud computing team at Google, where she saw cloud computing from the provider side.
Introduction to Deep Learning | CloudxLabCloudxLab
( Machine Learning & Deep Learning Specialization Training: https://goo.gl/goQxnL )
This CloudxLab Deep Learning tutorial helps you to understand Deep Learning in detail. Below are the topics covered in this tutorial:
1) What is Deep Learning
2) Deep Learning Applications
3) Artificial Neural Network
4) Deep Learning Neural Networks
5) Deep Learning Frameworks
6) AI vs Machine Learning
Scratch Workshop at Riverside School, Ahmedabad - By GSC DAIICTShreyans Gandhi
This is the presentation made by me at the Scratch Software Workshop conducted at the Riverside School, Ahmedabad.
The aim of the workshop was to get the grade 7 students know what amazing they can do with Scratch Software.
Video and slides synchronized, mp3 and slide download available at URL https://bit.ly/2SXXXiD.
Katharina Probst talks about what it means to act like an owner and why teams need ownership to be high-performing. When team members, regardless of whether they have a formal leadership role or not, act like owners, magical things can happen. She shares ideas that we can apply to our own work, and talks about how to recognize when we don’t live up to our own expectations of acting like an owner. Filmed at qconsf.com.
Katharina Probst is a Senior Engineering Leader, Kubernetes & SaaS at Google. Before this, she was leading engineering teams at Netflix, being responsible for the Netflix API, which helps bring Netflix streaming to millions of people around the world. Prior to joining Netflix, she was in the cloud computing team at Google, where she saw cloud computing from the provider side.
Introduction to Deep Learning | CloudxLabCloudxLab
( Machine Learning & Deep Learning Specialization Training: https://goo.gl/goQxnL )
This CloudxLab Deep Learning tutorial helps you to understand Deep Learning in detail. Below are the topics covered in this tutorial:
1) What is Deep Learning
2) Deep Learning Applications
3) Artificial Neural Network
4) Deep Learning Neural Networks
5) Deep Learning Frameworks
6) AI vs Machine Learning
We've all been there - we have a great plan for our workshop and then the loudspeaker, the derailer, the blocker or the silent one disrupts the flow. This talk helps with some tips to navigate those moments.
Volunteers make open source projects go. This talk discusses how to attract volunteers, what to do once you have, and how to keep them happy once you've got them.
Slides from a session at the American Alliance of Museums 2014 annual meeting, "Tech Tutorial: User Testing on a Shoestring (Beginners)."
Session presenters:
Christina DePaolo
Dana Mitroff Silvers
Charlotte Sexton
http://www.aam-us.org/events/annual-meeting/program/sessions-and-events?ID=2353
Knowing how to use Tableau doesn’t mean you'll be able to design effective dashboards. If you want to create dashboards that deliver valuable insight, perform well, and have visual impact, you'll need to apply Data Visualization Best Practices.
In this webinar, you'll learn the science behind Data Visualization Best Practices. Cognitive psychology helps us understand how the human brain perceives information in a dashboard, and we'll teach you how to use this knowledge to optimize your designs.
Creating a Data Driven L&D Team - an xAPI Case Study - DevLearn 2018Margaret Roth
From an organization-wide executive directive to become more data-driven, a retail corporate L&D team took an internal look at their own data practices. Realizing that they had an overwhelming lack of transparency into their learning initiatives and a great amount of data that had gone unused, the team developed a transformation vision to create a single system of record for learning to enable observability, granularity, and accountability for all team members. The team was committed to the vision of xAPI; however, the data and information they needed in order to make actionable change for their learners was locked away in non-interoperable formats, and they recognized the need to develop a data strategy and implementation plan.
In this case study session, you will see how the organization’s L&D team created an xAPI data roadmap to not only achieve early wins when it came to the executive business objectives but also begin work on a scalable plan to build out a modern, flexible ecosystem that has the needs of learners at its center.
* Originally presented on 10/25/18 at DevLearn by Allie Tscheulin and Margaret Roth
Getting Started with Big Data and SplunkTom Chavez
A beginner's introduction to the topic of Big Data, where you find it, how to get it into Splunk, and how to search it and get insights once it is this. Take an investigative journey through my mailbox as I seek to find out which messages could be deleted to make the biggest impact on reducing its footprint before my privileges are cut off!
This workshop is a precursor to creating full, research-backed personas, and is aimed to externalize what stakeholders already know about their customers - to share prior knowledge and assumptions through experience working at your company, interacting with users, and data generated by users. The provisional personas developed here are also known as: Proto-Personas, Ad Hoc Personas, Strawman Personas, Skeletal Personas, or Pragmatic Personas.
Assistive system for Parkinson's patients - Carnegie Mellon University Spring...KP Kshitij Parashar
The prototype was conceptualized, designed, and developed during Rapid Prototyping of Computer Systems course at Carnegie Mellon University in Spring 2020. I led the Interactions team in the final phase of the course.
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We've all been there - we have a great plan for our workshop and then the loudspeaker, the derailer, the blocker or the silent one disrupts the flow. This talk helps with some tips to navigate those moments.
Volunteers make open source projects go. This talk discusses how to attract volunteers, what to do once you have, and how to keep them happy once you've got them.
Slides from a session at the American Alliance of Museums 2014 annual meeting, "Tech Tutorial: User Testing on a Shoestring (Beginners)."
Session presenters:
Christina DePaolo
Dana Mitroff Silvers
Charlotte Sexton
http://www.aam-us.org/events/annual-meeting/program/sessions-and-events?ID=2353
Knowing how to use Tableau doesn’t mean you'll be able to design effective dashboards. If you want to create dashboards that deliver valuable insight, perform well, and have visual impact, you'll need to apply Data Visualization Best Practices.
In this webinar, you'll learn the science behind Data Visualization Best Practices. Cognitive psychology helps us understand how the human brain perceives information in a dashboard, and we'll teach you how to use this knowledge to optimize your designs.
Creating a Data Driven L&D Team - an xAPI Case Study - DevLearn 2018Margaret Roth
From an organization-wide executive directive to become more data-driven, a retail corporate L&D team took an internal look at their own data practices. Realizing that they had an overwhelming lack of transparency into their learning initiatives and a great amount of data that had gone unused, the team developed a transformation vision to create a single system of record for learning to enable observability, granularity, and accountability for all team members. The team was committed to the vision of xAPI; however, the data and information they needed in order to make actionable change for their learners was locked away in non-interoperable formats, and they recognized the need to develop a data strategy and implementation plan.
In this case study session, you will see how the organization’s L&D team created an xAPI data roadmap to not only achieve early wins when it came to the executive business objectives but also begin work on a scalable plan to build out a modern, flexible ecosystem that has the needs of learners at its center.
* Originally presented on 10/25/18 at DevLearn by Allie Tscheulin and Margaret Roth
Getting Started with Big Data and SplunkTom Chavez
A beginner's introduction to the topic of Big Data, where you find it, how to get it into Splunk, and how to search it and get insights once it is this. Take an investigative journey through my mailbox as I seek to find out which messages could be deleted to make the biggest impact on reducing its footprint before my privileges are cut off!
This workshop is a precursor to creating full, research-backed personas, and is aimed to externalize what stakeholders already know about their customers - to share prior knowledge and assumptions through experience working at your company, interacting with users, and data generated by users. The provisional personas developed here are also known as: Proto-Personas, Ad Hoc Personas, Strawman Personas, Skeletal Personas, or Pragmatic Personas.
Assistive system for Parkinson's patients - Carnegie Mellon University Spring...KP Kshitij Parashar
The prototype was conceptualized, designed, and developed during Rapid Prototyping of Computer Systems course at Carnegie Mellon University in Spring 2020. I led the Interactions team in the final phase of the course.
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
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Talk Delivered at Valencia Codes Meetup 2024-06.
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Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdfGetInData
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Why do we need yet another (open-source ) Copilot?
How can we build one?
Architecture and evaluation
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You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
11. Hey I just met you,
And this is crazy
But here’s my data.
Run an algorithm
on it, maybe?
- Carly Rae Jepsen
12. DBSCAN
● Density-based spatial
clustering of
applications with
noise.
● Two parameters:
○ How close the points
have to be?
○ How many points at
least a cluster should
have?
24. Turn your insights into knowledge
Translate results to accessible language
25. On the first day after sign up,
there are five main user types:
Ingrid,
the Inactive
Ellen,
the Excited
Alex,
the Athlete
Lucas,
the Lost
Nina,
the Novice
Doesn’t do
anything
Just configures
the study plan
Focus on
exercises:
25+ exercises
Tests a bit of the
platform:
2 Videos and 1
exercise
Really engaged:
study plan +
8 videos +
8 exercises