#ATAGTR2018 Presentation "The Subtle Influence of Cognitive Biases on Testing...Agile Testing Alliance
Prabhakar Panditi who is an enterprise Agile Coach, Executive Coach Lean Agile and Product Development Consult has conducted a Game session on "The Subtle Influence of Cognitive Biases on Testing Professional."
please refer our linkedin post for session details
https://www.linkedin.com/pulse/game-session-prabhaker-panditi-subtle-influence-biases-alliance/
The presentation lists a variety of proven tools for innovation management. The methods can be applied in different aspects of innovation including processes, solving problems, enhancing creativity, and Leadership. They also support the definition of strategy, decision making and evaluation. Furthermore it refers to a number of methods such a TRIZ, lean innovation and others.
New perspectives in innovation methods. A collection of 40 methods every manager must know to foster innovation. It includes a brief description of practical ways to use triz, design thinking, scrum, balacend scorecard an many others.
#ATAGTR2018 Presentation "The Subtle Influence of Cognitive Biases on Testing...Agile Testing Alliance
Prabhakar Panditi who is an enterprise Agile Coach, Executive Coach Lean Agile and Product Development Consult has conducted a Game session on "The Subtle Influence of Cognitive Biases on Testing Professional."
please refer our linkedin post for session details
https://www.linkedin.com/pulse/game-session-prabhaker-panditi-subtle-influence-biases-alliance/
The presentation lists a variety of proven tools for innovation management. The methods can be applied in different aspects of innovation including processes, solving problems, enhancing creativity, and Leadership. They also support the definition of strategy, decision making and evaluation. Furthermore it refers to a number of methods such a TRIZ, lean innovation and others.
New perspectives in innovation methods. A collection of 40 methods every manager must know to foster innovation. It includes a brief description of practical ways to use triz, design thinking, scrum, balacend scorecard an many others.
How to Become a Data Scientist | Data Scientist Skills | Data Science Trainin...Edureka!
** Data Science Master's Program: https://www.edureka.co/masters-program/data-scientist-certification **
This video on "How to become a Data Scientist" includes all the skills required for becoming a modern day Data Scientist. This video will answer the below questions:
1. Why should you go for data science?
2. What is the roadmap to become a data scientist?
3. What are the tools and techniques required to become a data scientist?
4. What are the roles of a data scientist?
Subscribe to our channel to get video updates. Hit the subscribe button above and click on the bell icon.
Check out our Data Science Training Playlist: https://goo.gl/Jg1pJJ
Presentation for the PNI Institute on the development of continuous applications of storysharing, sensemaking and change management with examples in Healthcare and Public Transport.
(Heartifacts) Continuous Improvement: Living with ADHDAaron Aldrich
(From April 2018, but I apparently forgot to punlish) Following DevOpsDays Hartford, my own mental illness took over for a couple of days. Like the past, it took me out of commission, but the lessons I've learned through dealing with myself, plus dealing with other complex systems, helped me recover faster and with less fallout.
A3 Thinking:
A3 thinking is a structured technique of working through problems or opportunities for improvement. The ‘A3’ itself is literally just that: a piece of A3 paper summarising the logical thought processes that have been agreed by the team in defining the opportunity for improvement or solving the problem they face.
HPX44- The True Power of User ResearchStella Hsiao
In this slide, you'll learn how to use qualitative and quantitative UX research data to boost team work and help generating idea that can growth your target index!
Workforce Intelligence: How HR Can Make Data-Driven Decisions That Move the N...Human Capital Media
The idea of data-driven HR has been a top topic and trend for several years now, yet the vast majority of HR organizations are still underserved with insights. While many organizations are thinking about workforce analytics, few have truly put them to work. Indeed, as Josh Bersin of Bersin by Deloitte aptly described, most HR organizations are “stuck in neutral” with workforce analytics, unsure how to get started with this complex topic.
How can you get out of neutral with workforce analytics? How can you and your organization overcome the data hurdles and technical complexity -- despite having little or no experience in analytics? How can you get to workforce insights that will help you understand with precision what it takes to recruit, retain, and motivate the best workforce -- and drive measurable business outcomes?
In this webinar, analytics expert Ian Cook will provide direct examples of you can take to:
Improve recruitment success and more efficiently find expertise needed at the right time for the best price.
Retain star performers more cost effectively.
Connect employee engagement to business outcomes.
Decode workforce planning and understand the “cost” side of the workforce.
People Analytics: Improving the Employee Experience and ProductivityDr Susan Entwisle
It is true today more than any point in history that talent is a company’s greatest asset. To thrive in our hyper competitive global economy, companies need the right talent to deliver exceptional customer experiences efficiently with minimal risk. Traditionally, Human Resource teams have made decisions on hiring, assigning and developing employees using experience, instinct, and basic statistical data. The same advanced analytics and machine learning techniques we use to improve the customer experience are now being used for our people. People analytics provides insights and enables better and faster data-driven decision making across all aspects of people at work.
Topics covered in this presentation include:
How analytics has changed the customer experience.
Current state of employee engagement and its impact.
Limitations of cognitive decision making process.
What is people analytics?
How companies are using people analytics today?
Challenges in adoption of people analytics.
Guidance to get started on people analytics journey.
Big data, evidence-based, predictive analytics, today these terms are all over the place. Is this just another fad or an irreversible trend? An increasing group of HR leaders relies on science, critical thinking and data analyses to make decisions.
Evidence-based HR, however, is still perceived by many as too time-consuming, narrow or impractical. Meanwhile, evidence-based practice is becoming mainstream in many other disciplines (like medicine). This is the momentum for pioneering HR leaders to seize the opportunity and make a difference with evidence. As part of an inclusive approach, valuing different perspectives.
We will enter into the dialogue about the why, the what, and most of all the how of evidence-based HR. How to get started and how to blend it with softer, less tangible HR practices? A pragmatic introduction, with realistic ambitions and openness towards other approaches.
LFS302_Real-World Evidence Platform to Enable Therapeutic InnovationAmazon Web Services
Historically, there has been an information asymmetry in pharmaceutical R&D where the biopharmaceutical companies had the deepest understanding and knowledge about their products and how they helped and interacted with patients. Now, there's new, real-world data that exists from regulators, health plans, government authorities, and patients, which is helping pharma companies to understand how their therapies and their innovations drive value and impact in patient populations. There are imperatives to leverage that data, create new partnerships in their ecosystem, and get access to that data in an ethical way to derive insights to both fuel innovation and drive discovery. In this session, you learn best practices from Deloitte and Celgene about strategy, operating models, and execution frameworks when implementing a real-world, evidence data platform.
How To Build a Winning Experimentation Program & Team | Optimizely ANZ Webinar 8Optimizely
Watch Dan Ross, Managing Director for Optimizely ANZ in our latest webinar from the Experimentation Insights Tour -- "How To Build a Winning Experimentation Program & Team."
View the presentation here: https://optimizely.wistia.com/medias/1o6xy4j0xm
Take Optimizely's Maturity Assessment here: https://www.optimizely.com/maturity-model/
DESCRIPTION: The world’s leading companies utilise experimentation to build a culture that fosters innovation and agility. The key to experimentation is to have both the right tools (software) in combination with the right people and processes
In this webinar, you will learn:
* Why experimentation is central to competing and innovating
* Areas to assess when building your experimentation capability
* How organisational culture helps scale an experimentation program
About Optimizely:
Optimizely is the world's leading experimentation platform, enabling businesses to deliver continuous experimentation and personalisation across websites, mobile apps and connected devices. Optimizely enables businesses to experiment deeply into their technology stack and broadly across the entire customer experience.
The platform’s ease of use and speed of deployment empower organisations to create and run bold experiments that help them make data-driven decisions and grow faster.
To date, marketers, developers and product managers have delivered over 700 billion experiences tailored to the needs of their customers. Optimizely’s global client base includes Atlassian, eBay, Fox, IBM, The New York Times, LendingClub, Hotwire, Microsoft and many more leading businesses.
To learn more about customer experience optimisation, visit optimizely.com
“How do you know so much about our program?” was a question the quality manager asked after reading the assessment report. The assessment took one day with eight interviews.
The reliability that results is going to happen whether or not the team designing the product or production line deliberately use reliability engineering tools or not. The elements of a product or system will respond to the environment and either work or fail.
SXSWedu 2018: Making Critical Thinking Real with Digital ContentJulie Evans
Everyone from employers to educators are talking about the need for today’s students to develop effective critical thinking and problem solving skills-but few people know what that really looks like in a classroom or how to measure student competency in a meaningful way. This workshop is designed to take the conceptual understanding of critical thinking to a more practical reality. Grounded in research about employers’ expectations and educators’ challenges in this area, the workshop will use innovative digital content and games to demonstrate how students can effectively develop problem solving muscles, and how teachers can measure student competencies. Features Arts, Science and Civics.
From Dr. Julie Evans (Project Tomorrow) and Dr. Kari Stubbs (BrainPOP)
Measuring Success: Which Customer Focused Initiative is the Right One?
You've gone beyond segmentation and have done some qualitative research to understand what consumers really need and want from your organization. You've used those research insights to envision an improved consumer journey that will alleviate pain points and even deliver delight! The team is on the same page that this vision will result in a fundamentally improved experience. But there are many aspects of the journey. Many changes will need to be made, some large and some small. Which are more important? Which will get you the most results? What should be done first, second, and third? Where should limited investment dollars be spent? This talk will explore key considerations for measuring consumer engagement, deciding which metrics are important to your organization, and how to set up guiding principles as a framework for decision making.
How to Become a Data Scientist | Data Scientist Skills | Data Science Trainin...Edureka!
** Data Science Master's Program: https://www.edureka.co/masters-program/data-scientist-certification **
This video on "How to become a Data Scientist" includes all the skills required for becoming a modern day Data Scientist. This video will answer the below questions:
1. Why should you go for data science?
2. What is the roadmap to become a data scientist?
3. What are the tools and techniques required to become a data scientist?
4. What are the roles of a data scientist?
Subscribe to our channel to get video updates. Hit the subscribe button above and click on the bell icon.
Check out our Data Science Training Playlist: https://goo.gl/Jg1pJJ
Presentation for the PNI Institute on the development of continuous applications of storysharing, sensemaking and change management with examples in Healthcare and Public Transport.
(Heartifacts) Continuous Improvement: Living with ADHDAaron Aldrich
(From April 2018, but I apparently forgot to punlish) Following DevOpsDays Hartford, my own mental illness took over for a couple of days. Like the past, it took me out of commission, but the lessons I've learned through dealing with myself, plus dealing with other complex systems, helped me recover faster and with less fallout.
A3 Thinking:
A3 thinking is a structured technique of working through problems or opportunities for improvement. The ‘A3’ itself is literally just that: a piece of A3 paper summarising the logical thought processes that have been agreed by the team in defining the opportunity for improvement or solving the problem they face.
HPX44- The True Power of User ResearchStella Hsiao
In this slide, you'll learn how to use qualitative and quantitative UX research data to boost team work and help generating idea that can growth your target index!
Workforce Intelligence: How HR Can Make Data-Driven Decisions That Move the N...Human Capital Media
The idea of data-driven HR has been a top topic and trend for several years now, yet the vast majority of HR organizations are still underserved with insights. While many organizations are thinking about workforce analytics, few have truly put them to work. Indeed, as Josh Bersin of Bersin by Deloitte aptly described, most HR organizations are “stuck in neutral” with workforce analytics, unsure how to get started with this complex topic.
How can you get out of neutral with workforce analytics? How can you and your organization overcome the data hurdles and technical complexity -- despite having little or no experience in analytics? How can you get to workforce insights that will help you understand with precision what it takes to recruit, retain, and motivate the best workforce -- and drive measurable business outcomes?
In this webinar, analytics expert Ian Cook will provide direct examples of you can take to:
Improve recruitment success and more efficiently find expertise needed at the right time for the best price.
Retain star performers more cost effectively.
Connect employee engagement to business outcomes.
Decode workforce planning and understand the “cost” side of the workforce.
People Analytics: Improving the Employee Experience and ProductivityDr Susan Entwisle
It is true today more than any point in history that talent is a company’s greatest asset. To thrive in our hyper competitive global economy, companies need the right talent to deliver exceptional customer experiences efficiently with minimal risk. Traditionally, Human Resource teams have made decisions on hiring, assigning and developing employees using experience, instinct, and basic statistical data. The same advanced analytics and machine learning techniques we use to improve the customer experience are now being used for our people. People analytics provides insights and enables better and faster data-driven decision making across all aspects of people at work.
Topics covered in this presentation include:
How analytics has changed the customer experience.
Current state of employee engagement and its impact.
Limitations of cognitive decision making process.
What is people analytics?
How companies are using people analytics today?
Challenges in adoption of people analytics.
Guidance to get started on people analytics journey.
Big data, evidence-based, predictive analytics, today these terms are all over the place. Is this just another fad or an irreversible trend? An increasing group of HR leaders relies on science, critical thinking and data analyses to make decisions.
Evidence-based HR, however, is still perceived by many as too time-consuming, narrow or impractical. Meanwhile, evidence-based practice is becoming mainstream in many other disciplines (like medicine). This is the momentum for pioneering HR leaders to seize the opportunity and make a difference with evidence. As part of an inclusive approach, valuing different perspectives.
We will enter into the dialogue about the why, the what, and most of all the how of evidence-based HR. How to get started and how to blend it with softer, less tangible HR practices? A pragmatic introduction, with realistic ambitions and openness towards other approaches.
LFS302_Real-World Evidence Platform to Enable Therapeutic InnovationAmazon Web Services
Historically, there has been an information asymmetry in pharmaceutical R&D where the biopharmaceutical companies had the deepest understanding and knowledge about their products and how they helped and interacted with patients. Now, there's new, real-world data that exists from regulators, health plans, government authorities, and patients, which is helping pharma companies to understand how their therapies and their innovations drive value and impact in patient populations. There are imperatives to leverage that data, create new partnerships in their ecosystem, and get access to that data in an ethical way to derive insights to both fuel innovation and drive discovery. In this session, you learn best practices from Deloitte and Celgene about strategy, operating models, and execution frameworks when implementing a real-world, evidence data platform.
How To Build a Winning Experimentation Program & Team | Optimizely ANZ Webinar 8Optimizely
Watch Dan Ross, Managing Director for Optimizely ANZ in our latest webinar from the Experimentation Insights Tour -- "How To Build a Winning Experimentation Program & Team."
View the presentation here: https://optimizely.wistia.com/medias/1o6xy4j0xm
Take Optimizely's Maturity Assessment here: https://www.optimizely.com/maturity-model/
DESCRIPTION: The world’s leading companies utilise experimentation to build a culture that fosters innovation and agility. The key to experimentation is to have both the right tools (software) in combination with the right people and processes
In this webinar, you will learn:
* Why experimentation is central to competing and innovating
* Areas to assess when building your experimentation capability
* How organisational culture helps scale an experimentation program
About Optimizely:
Optimizely is the world's leading experimentation platform, enabling businesses to deliver continuous experimentation and personalisation across websites, mobile apps and connected devices. Optimizely enables businesses to experiment deeply into their technology stack and broadly across the entire customer experience.
The platform’s ease of use and speed of deployment empower organisations to create and run bold experiments that help them make data-driven decisions and grow faster.
To date, marketers, developers and product managers have delivered over 700 billion experiences tailored to the needs of their customers. Optimizely’s global client base includes Atlassian, eBay, Fox, IBM, The New York Times, LendingClub, Hotwire, Microsoft and many more leading businesses.
To learn more about customer experience optimisation, visit optimizely.com
“How do you know so much about our program?” was a question the quality manager asked after reading the assessment report. The assessment took one day with eight interviews.
The reliability that results is going to happen whether or not the team designing the product or production line deliberately use reliability engineering tools or not. The elements of a product or system will respond to the environment and either work or fail.
SXSWedu 2018: Making Critical Thinking Real with Digital ContentJulie Evans
Everyone from employers to educators are talking about the need for today’s students to develop effective critical thinking and problem solving skills-but few people know what that really looks like in a classroom or how to measure student competency in a meaningful way. This workshop is designed to take the conceptual understanding of critical thinking to a more practical reality. Grounded in research about employers’ expectations and educators’ challenges in this area, the workshop will use innovative digital content and games to demonstrate how students can effectively develop problem solving muscles, and how teachers can measure student competencies. Features Arts, Science and Civics.
From Dr. Julie Evans (Project Tomorrow) and Dr. Kari Stubbs (BrainPOP)
Measuring Success: Which Customer Focused Initiative is the Right One?
You've gone beyond segmentation and have done some qualitative research to understand what consumers really need and want from your organization. You've used those research insights to envision an improved consumer journey that will alleviate pain points and even deliver delight! The team is on the same page that this vision will result in a fundamentally improved experience. But there are many aspects of the journey. Many changes will need to be made, some large and some small. Which are more important? Which will get you the most results? What should be done first, second, and third? Where should limited investment dollars be spent? This talk will explore key considerations for measuring consumer engagement, deciding which metrics are important to your organization, and how to set up guiding principles as a framework for decision making.
At the Advertising Research Foundation’s (ARF) 2011 Annual re:think convention, Richard Thorogood-Director of Strategic Insights and Analytics for Colgate Palmolive presented sponsor feedback on the NeuroStandards Collaboration Project
Developing Emotional Intelligence Skills for High Performance CulturesHuman Capital Media
More and more of the leading executives are creating high performing cultures with mindfulness. There is a very simple reason for this: in the modern business, EQ is more important than IQ. EQ, or “emotional intelligence,” is highly trainable through a variety of mindfulness and positive psychology techniques.
Join Whil, the leaders in digital mindfulness training, to find out:
What mindfulness training is and how to bring it to your employees
The secrets of the emotional intelligence and leadership training born at Google
How to unleash the leadership potential in your team, including millennials
How mindfulness can help your employees thrive, in the face of of stress and disruption
All attendees will get a free special eBook and a subscription to Whil’s digital training platform, featuring thousands of training programs based in neuroscience, mindfulness and positive psychology.
Similar to Data, Artificial Intelligence, and Analytics for Star Rating Success (20)
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeWalaa Eldin Moustafa
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
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).
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Global Situational Awareness of A.I. and where its headedvikram sood
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.
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
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.
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.
Unleashing the Power of Data_ Choosing a Trusted Analytics Platform.pdfEnterprise Wired
In this guide, we'll explore the key considerations and features to look for when choosing a Trusted analytics platform that meets your organization's needs and delivers actionable intelligence you can trust.
10. Moving from WHAT is being said to HOW it is being said.
Response
Sentiment
Theme
Categorization
Topic
WHAT
Source: International Journal of Science Technology and Management
http://www.ijstm.com/images/short_pdf/1480737677_541ijstm.pdf
Authentication examples: Twilio, Nice
11. Moving from WHAT is being said to HOW it is being said.
Tone
Enunciation
Pitch
Emotion
Patterns
Authentication
Response
Sentiment
Theme
Categorization
Topic
WHAT HOW
+
Source: International Journal of Science Technology and Management
http://www.ijstm.com/images/short_pdf/1480737677_541ijstm.pdf
Authentication examples: Twilio, Nice
12. Text analysis tools are smart enough to determine written context.
Example: https://cloud.google.com/natural-language/
13. Text analysis tools smart enough to determine written context.
Example: https://cloud.google.com/natural-language/
14. Allows analytics routing to take appropriate action steps.
I have been depressed, lately.
My mouth has been really dry, even
though I’m drinking lots of water.
Physiological
Psychological
20. Combine Traditional with New NLP methods
to drive Star Ratings
+ =
What How
+“I don’t think so.” Sense Hesitation
21. Enable NLP Analytics through mix of data science tools and APIs.
HOW - Analyze the sonic profile.WHAT - Analyze words/tokens.
+
Sources:
International Journal of Science Technology and Management
http://www.ijstm.com/images/short_pdf/1480737677_541ijstm.pdf
http://www.beyondverbal.com/api/
https://www.nice.com/engage/customer-analytics/speech-analytics
Sources:
https://cloud.google.com/natural-language/
https://aws.amazon.com/amazon-ai/
Enable via:
Vendors: eg.
BeyondVerbal,
Nice
R packages:
tuner, seewave,
playitbyr, &
audiolyzR
Google NLP
API
Amazon Lex,
Amazon
Polly
Python NLTK
R – NLP