Vivek Prahlad shares his experiences on the differences and similarities between building software in the Product and Project contexts. At ThoughtWorks, he has spent approximately half of his career on the product side, and the other half on the consulting side. While the underlying principles are similar, there are often significant differences in terms of approaches that work for products and projects. Some of the differences we'll explore include: product vs. project inception, engineering considerations, testing approaches and strategies, course corrections, and more.
Exhibitor Insights: RFID in Fashion Retail: The Key Driver for Delivering Wha...National Retail Federation
Exhibitor Insights Session; RFID in Fashion Retail: The Key Driver for Delivering What Customers Want
Juha Reima, NordicID
Rich Haig, Herman Kay
Paul Murdock, NordicID
Presentation from Retail’s BIG Show, January 15-17, 2017.
GLENN ALLISON, VP, Enterprise Architecture and IT Solution Delivery,
Tractor Supply Company
SCOTT EMMONS, Director and Founder, Innovation Lab, The Neiman Marcus Group, Inc.
MICHAEL STRAUSE, Dir., Architecture and Engineering, Tory Burch
Vivek Prahlad shares his experiences on the differences and similarities between building software in the Product and Project contexts. At ThoughtWorks, he has spent approximately half of his career on the product side, and the other half on the consulting side. While the underlying principles are similar, there are often significant differences in terms of approaches that work for products and projects. Some of the differences we'll explore include: product vs. project inception, engineering considerations, testing approaches and strategies, course corrections, and more.
Exhibitor Insights: RFID in Fashion Retail: The Key Driver for Delivering Wha...National Retail Federation
Exhibitor Insights Session; RFID in Fashion Retail: The Key Driver for Delivering What Customers Want
Juha Reima, NordicID
Rich Haig, Herman Kay
Paul Murdock, NordicID
Presentation from Retail’s BIG Show, January 15-17, 2017.
GLENN ALLISON, VP, Enterprise Architecture and IT Solution Delivery,
Tractor Supply Company
SCOTT EMMONS, Director and Founder, Innovation Lab, The Neiman Marcus Group, Inc.
MICHAEL STRAUSE, Dir., Architecture and Engineering, Tory Burch
National Retail Federation
Retail's BIG Show
January 15-17, 2017
TRISTAN POLLOCK, EIR/Venture Partner, 500 Startups
CHRISTOPHER GAVIGAN, Founder and Chief Purpose Officer, The Honest Company
LARS PETERSSON, President, IKEA US
Presentation from Retail’s BIG Show, January 15-17, 2017.
GORDON DAVIDSON, CEO, Cloverleaf
JAMIE GLIDDEN, Dir., North America Retail, Dell Technologies
GABI ZIJDERVELD, CMO, Affectiva
Retail's BIG Show
January 15-17, 2017
GREG BUZEK, President, IHL Group
JEFF ROSTER, VP, Strategy, IHL Group
DAVID STROBELT, SVP/CIO, Modell’s Sporting Goods
SCOTT EMMONS, Director and Founder, Innovation Lab, The Neiman Marcus Group
Exhibitor Insights from Retail's BIG Show 2017. Small Parcel Shipping costs have soared over 35% in the past 5 years. LTL carriers are imposing sharp rate hikes annually. At the same time, Retail customers are hyper sensitive to shipping costs and have come to expect 'free shipping'. How do Retailers stay competitive with their shipping costs?
Retail's BIG Show
January 15-17, 2017
What's Hiding in Your Point of Sale Data?
Irad Ben-Gal, Stanford University/C-B4
Miki Cisic, C-B4 Analytics
Joe Gauthier, Wesco, Inc.
Exhibitor Insights session. Monday, January 16, 2017
Creating MEaningful Experiences - Unifying Digital Journeys
Hari Shetty, Wipro'
Dawn Gillis, 7-Eleven, Inc.
George Anderson, RetailWire
Ratnakar Lavu, Kohl's
Exhibitor Insights Presentation from Retail’s BIG Show, January 15-17, 2017.
The right technology can help rapidly unify commerce. Learn how cloud-based solutions on a single platform quickly integrate & improve customer engagement and sales.
JIM BARNES, CEO, Enspire Commerce
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
Our Services Include:
Reporting to Tracking Authorities:
We immediately notify all relevant centralized exchanges (CEX), decentralized exchanges (DEX), and wallet providers about the stolen cryptocurrency. This ensures that the stolen assets are flagged as scam transactions, making it impossible for the thief to use them.
Assistance with Filing Police Reports:
We guide you through the process of filing a valid police report. Our support team provides detailed instructions on which police department to contact and helps you complete the necessary paperwork within the critical 72-hour window.
Launching the Refund Process:
Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
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.
How can I successfully sell my pi coins in Philippines?DOT TECH
Even tho pi not launched globally, crypto whales, holders, investors are looking forward to hold up to 20,000 pi coins before mainnet launch in 2026.
All a miner or pioneer has to do to sell is to get in contact with a legitimate pi vendor ( a person that buys pi coins from miners and resell them to investors)
I will leave the telegram contact of my personal pi vendor:
@Pi_vendor_247
#pi network
#pi 2024
#sell pi
National Retail Federation
Retail's BIG Show
January 15-17, 2017
TRISTAN POLLOCK, EIR/Venture Partner, 500 Startups
CHRISTOPHER GAVIGAN, Founder and Chief Purpose Officer, The Honest Company
LARS PETERSSON, President, IKEA US
Presentation from Retail’s BIG Show, January 15-17, 2017.
GORDON DAVIDSON, CEO, Cloverleaf
JAMIE GLIDDEN, Dir., North America Retail, Dell Technologies
GABI ZIJDERVELD, CMO, Affectiva
Retail's BIG Show
January 15-17, 2017
GREG BUZEK, President, IHL Group
JEFF ROSTER, VP, Strategy, IHL Group
DAVID STROBELT, SVP/CIO, Modell’s Sporting Goods
SCOTT EMMONS, Director and Founder, Innovation Lab, The Neiman Marcus Group
Exhibitor Insights from Retail's BIG Show 2017. Small Parcel Shipping costs have soared over 35% in the past 5 years. LTL carriers are imposing sharp rate hikes annually. At the same time, Retail customers are hyper sensitive to shipping costs and have come to expect 'free shipping'. How do Retailers stay competitive with their shipping costs?
Retail's BIG Show
January 15-17, 2017
What's Hiding in Your Point of Sale Data?
Irad Ben-Gal, Stanford University/C-B4
Miki Cisic, C-B4 Analytics
Joe Gauthier, Wesco, Inc.
Exhibitor Insights session. Monday, January 16, 2017
Creating MEaningful Experiences - Unifying Digital Journeys
Hari Shetty, Wipro'
Dawn Gillis, 7-Eleven, Inc.
George Anderson, RetailWire
Ratnakar Lavu, Kohl's
Exhibitor Insights Presentation from Retail’s BIG Show, January 15-17, 2017.
The right technology can help rapidly unify commerce. Learn how cloud-based solutions on a single platform quickly integrate & improve customer engagement and sales.
JIM BARNES, CEO, Enspire Commerce
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
Our Services Include:
Reporting to Tracking Authorities:
We immediately notify all relevant centralized exchanges (CEX), decentralized exchanges (DEX), and wallet providers about the stolen cryptocurrency. This ensures that the stolen assets are flagged as scam transactions, making it impossible for the thief to use them.
Assistance with Filing Police Reports:
We guide you through the process of filing a valid police report. Our support team provides detailed instructions on which police department to contact and helps you complete the necessary paperwork within the critical 72-hour window.
Launching the Refund Process:
Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
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.
How can I successfully sell my pi coins in Philippines?DOT TECH
Even tho pi not launched globally, crypto whales, holders, investors are looking forward to hold up to 20,000 pi coins before mainnet launch in 2026.
All a miner or pioneer has to do to sell is to get in contact with a legitimate pi vendor ( a person that buys pi coins from miners and resell them to investors)
I will leave the telegram contact of my personal pi vendor:
@Pi_vendor_247
#pi network
#pi 2024
#sell pi
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).
3. Introduction
Name – Sanjay Kumar Kantilal Mota
Email – skmota@gmail.com
Qualification – Bachelor of commerce, MBA (Finance), PG Diploma in Computers
Certifications – PRINCE2 Practitioner, ITIL Foundation, Microsoft Certified Professional, Siebel
Certified Consultant
Work Experience – 26 years of IT experience working with Mastek, Deloitte, GENPACT, Wipro,
Satyam, Accenture
Geographic Experience – India, UK, USA, Japan
Industry Experience – 6 years of Capital Market related projects
4. Artificial Intelligence
SourceData
• Historical
Price Data
• EOD
• Intraday
DataMining
• Encoding
• Decoding
MachineLearning
Algorithms
• Training
• Testing
• Classification
• Regression
• Prediction
Trading
• Automated
or Manual
• Intra-day
• Positional
High Level Process Flow
5. Daily Predictions
Based on historical End of Day price data using Data Mining, Machine Learning and AI
14 years of Training Data and 6 years of Test Data used
Predicts if next day closing will be higher or lower than the next day
opening levels
Accuracy of 59% for Nifty, 9% more than by random guessing
Profit from 59% Accurate Prediction 39862.15 points (871 days)
Loss from 41% In-Accurate prediction 23963.5 points (604 days)
Net profit 15898.65 points (Total 1475 days)
For large volume Accuracy can be improved to 63% i.e. 13% more than
by random guessing
Can be used for Manual or Automated Intraday Trading
Prediction available after closing of the current day market and before
opening of the next day market
6. For Prediction of Closing > Opening
Buy at and below opening Level
Can also be used to trade in Binary Options
Spread out the trade by creating additional buy
trade when price falls by certain units e.g. every 0.05
points
For Prediction of Closing < Opening
Sell at and above opening level
Can also be used in Binary Options
Spread out the trade by creating
additional sell trade when price rises
by certain units e.g. every 0.05 points
Suggested Automated Trading Approach
Close all open positions before close of Trading
Incremental spread of Trades by certain units will ensure higher profitability on
profitable days (59%) and lesser loss on loss making days (41%)
Intraday trading will provide for higher leverage and no overnight carry over
7. -
Target Customers
Plan to work with very few Large Trading Companies
• Instruments with Large Market Capitalization and Liquidity
• Different World Markets (FTSE, DJIA, S&P500, NIFTY …)
• Large Trading Position
Profitability
• Plan to charge % of profit share
8. The Service is offered as it is on profit sharing basis without taking any responsivity for any trading risk
and trading loss.
Data for the instruments to be traded has to be provided by Customer
The process used for predictive analytics using Data Mining, Machine Learning and AI are my IP rights
and should be respected accordingly
I am free to deal with other companies to use predictive analytics using Data Mining, Machine
Learning and AI for other instruments in same or other markets
Accuracy varies for each instrument and needs to checked based on historical price data
Future prediction might or might not follow the past performance
Important Notes
9. Cracking
Wall Street
Can
technology
build a
better
Buffett?
List of Funds
or Trading
Firms Using
Artificial
Intelligence
How
Computers
Trawl a Sea
of Data for
Stock Picks -
WSJ
Battle of the
Quants
Quants turn
to AI for
market
insights
Investor
rush to
artificial
intelligence
is real deal -
FT.com
AI That
Picks Stocks
Better Than
the Pros |
MIT
Technology
Israel's
Financial
Algorithms
Gets $4B
Buy Bid,
Calcalist
Says
The Rise of
the Tech
Model May
Soon Make
You
Obsolete
BlackRock
and Google
in talks over
joint
venture -
FT.com
Big banks
invest
$13.5M in
machine
learning
startup ..
Goldman
Sachs Leads
$15 Million
Investment
in Kensho ..
Artificial
intelligence
is the next
big thing for
hedge funds
Introducing
Binatix, a
Deep-
Learning
Trading Firm
That's ...
Algorithmic
Trading:
Swing
Trading
Based on
Machine ..
Forex
Scandal
Drives Shift
to Algo
Trading -
Wall Street
...
Interesting Readings