Following the release of the first PAMCo data (the new audience measurement currency for published media), we've been looking to see what the reach and engagement of magazine media means for a number of sectors. Here we take a look at the automotive sector.
Following the release of the first PAMCo data (the new audience measurement currency for published media), we've been looking to see what the reach and engagement of magazine media means for a number of sectors. Here we take a look at food.
Following the release of PAMCo data from March 2019, we've taken a look at the reach and engagement of magazine media for a number of sectors. Here we take a look at homes.
Market Overview - The Basics - March 2019 Louise Ioannou
All the magazine media stats you'll ever need in one handy download. The very best industry data is sourced from PAMCo, AA/WARC, ABC’s and NMR, and is updated quarterly.
All the magazine media stats you'll ever need in one handy download. The very best industry data is sourced from PAMCo, AA/WARC, ABC’s and NMR, and is updated quarterly.
Following the release of the first PAMCo data (the new audience measurement currency for published media), we've been looking to see what the reach and engagement of magazine media means for a number of sectors. Here we take a look at the automotive sector.
Following the release of the first PAMCo data (the new audience measurement currency for published media), we've been looking to see what the reach and engagement of magazine media means for a number of sectors. Here we take a look at food.
Following the release of PAMCo data from March 2019, we've taken a look at the reach and engagement of magazine media for a number of sectors. Here we take a look at homes.
Market Overview - The Basics - March 2019 Louise Ioannou
All the magazine media stats you'll ever need in one handy download. The very best industry data is sourced from PAMCo, AA/WARC, ABC’s and NMR, and is updated quarterly.
All the magazine media stats you'll ever need in one handy download. The very best industry data is sourced from PAMCo, AA/WARC, ABC’s and NMR, and is updated quarterly.
Following the release of the first PAMCo data (the new audience measurement currency for published media), we've been looking to see what the reach and engagement of magazine media means for a number of sectors. Here we take a look at the automotive sector.
PAMCo: a summary of data for the homes sectorLouise Ioannou
Following the release of the first PAMCo data (the new audience measurement currency for published media), we've been looking to see what the reach and engagement of magazine media means for a number of sectors. Here we take a look at homes.
All the magazine media stats you'll ever need in one handy download. The very best industry data is sourced from PAMCo, AA/WARC, ABC’s and NMR, and is updated quarterly.
Women Drivers: a missed opportunity for motors brandsLouise Ioannou
Women drivers are a missed opportunity for motor brands. Insight from Hearst shows that motor brands may be missing a trick with a female audience by focusing advertising on predominantly male magazine titles.
Following the release of the first PAMCo data (the new audience measurement currency for published media), we've been looking to see what the reach and engagement of magazine media means for a number of sectors.
Following the release of the first PAMCo data (the new audience measurement currency for published media), we've been looking to see what the reach and engagement of magazine media means for a number of sectors.
Following the release of the first PAMCo data (the new audience measurement currency for published media), we've been looking to see what the reach and engagement of magazine media means for a number of sectors.
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).
Following the release of the first PAMCo data (the new audience measurement currency for published media), we've been looking to see what the reach and engagement of magazine media means for a number of sectors. Here we take a look at the automotive sector.
PAMCo: a summary of data for the homes sectorLouise Ioannou
Following the release of the first PAMCo data (the new audience measurement currency for published media), we've been looking to see what the reach and engagement of magazine media means for a number of sectors. Here we take a look at homes.
All the magazine media stats you'll ever need in one handy download. The very best industry data is sourced from PAMCo, AA/WARC, ABC’s and NMR, and is updated quarterly.
Women Drivers: a missed opportunity for motors brandsLouise Ioannou
Women drivers are a missed opportunity for motor brands. Insight from Hearst shows that motor brands may be missing a trick with a female audience by focusing advertising on predominantly male magazine titles.
Following the release of the first PAMCo data (the new audience measurement currency for published media), we've been looking to see what the reach and engagement of magazine media means for a number of sectors.
Following the release of the first PAMCo data (the new audience measurement currency for published media), we've been looking to see what the reach and engagement of magazine media means for a number of sectors.
Following the release of the first PAMCo data (the new audience measurement currency for published media), we've been looking to see what the reach and engagement of magazine media means for a number of sectors.
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).
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
Learn SQL from basic queries to Advance queriesmanishkhaire30
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
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 OpenMP PageRank : SHORT REPORT / NOTESSubhajit Sahu
For massive graphs that fit in RAM, but not in GPU memory, it is possible to take
advantage of a shared memory system with multiple CPUs, each with multiple cores, to
accelerate pagerank computation. If the NUMA architecture of the system is properly taken
into account with good vertex partitioning, the speedup can be significant. To take steps in
this direction, experiments are conducted to implement pagerank in OpenMP using two
different approaches, uniform and hybrid. The uniform approach runs all primitives required
for pagerank in OpenMP mode (with multiple threads). On the other hand, the hybrid
approach runs certain primitives in sequential mode (i.e., sumAt, multiply).
Analysis insight about a Flyball dog competition team's performanceroli9797
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.