Category: Uncategorized

[  COVER OF THE WEEK ]

Conditional Risk  Source

[ LOCAL EVENTS & SESSIONS]

• Mar 20, 2019 #WEB Analytical Methods Validation for FDA Compliance
• Feb 20, 2019 #WEB Thinkful Webinar | Getting Started in Data Science
• Feb 27, 2019 #WEB Webinar – Implementing AI applications with Power BI

More WEB events? Click Here

[ AnalyticsWeek BYTES]

>> Battling Misinformation in Customer Experience Management by bobehayes

>> RSPB Conservation Efforts Take Flight Thanks To Data Analytics by analyticsweekpick

>> @SidProbstein / @AIFoundry on Leading #DataDriven Technology Transformation by v1shal

Wanna write? Click Here

[ NEWS BYTES]

>>
 North America Quality Management In Healthcare Market Growth Analysis, and Forecast Including Factors … – Industry Strategy Under  Health Analytics

>>
 New Orioles GM Mike Elias brings former Astros analytics chief Sig Mejdal along to Baltimore – Baltimore Sun Under  Analytics

>>
 Nutanix Joins IoT And Edge Computing Bandwagon With Xi IoT Platform – Forbes Under  IOT

More NEWS ? Click Here

[ FEATURED COURSE]

Probability & Statistics

This course introduces students to the basic concepts and logic of statistical reasoning and gives the students introductory-level practical ability to choose, generate, and properly interpret appropriate descriptive and… more

[ FEATURED READ]

Storytelling with Data: A Data Visualization Guide for Business Professionals

Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You’ll discover the power of storytelling and the way to make data a pivotal point in your story. Th… more

[ TIPS & TRICKS OF THE WEEK]

Data Have Meaning
We live in a Big Data world in which everything is quantified. While the emphasis of Big Data has been focused on distinguishing the three characteristics of data (the infamous three Vs), we need to be cognizant of the fact that data have meaning. That is, the numbers in your data represent something of interest, an outcome that is important to your business. The meaning of those numbers is about the veracity of your data.

[ DATA SCIENCE Q&A]

Q:How do you assess the statistical significance of an insight?
A: * is this insight just observed by chance or is it a real insight?
Statistical significance can be accessed using hypothesis testing:
– Stating a null hypothesis which is usually the opposite of what we wish to test (classifiers A and B perform equivalently, Treatment A is equal of treatment B)
– Then, we choose a suitable statistical test and statistics used to reject the null hypothesis
– Also, we choose a critical region for the statistics to lie in that is extreme enough for the null hypothesis to be rejected (p-value)
– We calculate the observed test statistics from the data and check whether it lies in the critical region

Common tests:
– One sample Z test
– Two-sample Z test
– One sample t-test
– paired t-test
– Two sample pooled equal variances t-test
– Two sample unpooled unequal variances t-test and unequal sample sizes (Welch’s t-test)
– Chi-squared test for variances
– Chi-squared test for goodness of fit
– Anova (for instance: are the two regression models equals? F-test)
– Regression F-test (i.e: is at least one of the predictor useful in predicting the response?)

Source

[ VIDEO OF THE WEEK]

 Discussing #InfoSec with @travturn, @hrbrmstr(@rapid7) @thebearconomist(@boozallen) @yaxa_io

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[ QUOTE OF THE WEEK]

Torture the data, and it will confess to anything. – Ronald Coase

[ PODCAST OF THE WEEK]

 #BigData @AnalyticsWeek #FutureOfData #Podcast with @ScottZoldi, @FICO

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[ FACT OF THE WEEK]

571 new websites are created every minute of the day.

Sourced from: Analytics.CLUB #WEB Newsletter

[  COVER OF THE WEEK ]

Conditional Risk  Source

[ LOCAL EVENTS & SESSIONS]

• Feb 22, 2019 #WEB Live-Webinar “Orientierung im Big Data Dschungel” mit Inga Ketels
• Feb 21, 2019 #WEB [REPLAY] How To Design a Patient-Centered Mobile Health App
• Feb 21, 2019 #WEB UKAT Research Showcase Webinar – Knowing you: Learning Analytics, the Johari Window and Personal Tutoring

More WEB events? Click Here

[ AnalyticsWeek BYTES]

>> Global Business By The Big Analytics – Playcast – Data Analytics Leadership Playbook Podcast by v1shal

>> Jason Carmel ( @defenestrate99 / @possible ) Leading Analytics, Data, Digital & Marketing by v1shal

>> It’s Official! Talend to Welcome Stitch to the Family! by analyticsweekpick

Wanna write? Click Here

[ NEWS BYTES]

>>
 Big Data Made Simple – insideBIGDATA Under  Big Data

>>
 India cannot afford to ignore Data Science – Economic Times (blog) Under  Data Science

>>
 Have you heard? Hybrid cloud is the ideal IT model – Information Age Under  Hybrid Cloud

More NEWS ? Click Here

[ FEATURED COURSE]

Intro to Machine Learning

Machine Learning is a first-class ticket to the most exciting careers in data analysis today. As data sources proliferate along with the computing power to process them, going straight to the data is one of the most stra… more

[ FEATURED READ]

The Signal and the Noise: Why So Many Predictions Fail–but Some Don’t

People love statistics. Statistics, however, do not always love them back. The Signal and the Noise, Nate Silver’s brilliant and elegant tour of the modern science-slash-art of forecasting, shows what happens when Big Da… more

[ TIPS & TRICKS OF THE WEEK]

Keeping Biases Checked during the last mile of decision making
Today a data driven leader, a data scientist or a data driven expert is always put to test by helping his team solve a problem using his skills and expertise. Believe it or not but a part of that decision tree is derived from the intuition that adds a bias in our judgement that makes the suggestions tainted. Most skilled professionals do understand and handle the biases well, but in few cases, we give into tiny traps and could find ourselves trapped in those biases which impairs the judgement. So, it is important that we keep the intuition bias in check when working on a data problem.

[ DATA SCIENCE Q&A]

Q:How to detect individual paid accounts shared by multiple users?
A: * Check geographical region: Friday morning a log in from Paris and Friday evening a log in from Tokyo
* Bandwidth consumption: if a user goes over some high limit
* Counter of live sessions: if they have 100 sessions per day (4 times per hour) that seems more than one person can do

Source

[ VIDEO OF THE WEEK]

 @JohnTLangton from @Wolters_Kluwer discussed his #AI Lead Startup Journey #FutureOfData #Podcast

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[ QUOTE OF THE WEEK]

Numbers have an important story to tell. They rely on you to give them a voice. – Stephen Few

[ PODCAST OF THE WEEK]

 #BigData @AnalyticsWeek #FutureOfData #Podcast with @Beena_Ammanath, @GE

Subscribe 

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[ FACT OF THE WEEK]

Every person in the US tweeting three tweets per minute for 26,976 years.

Sourced from: Analytics.CLUB #WEB Newsletter

[  COVER OF THE WEEK ]

Convincing  Source

[ LOCAL EVENTS & SESSIONS]

• Feb 06, 2019 #WEB Online Meetup: Best Practices for Kubernetes
• Feb 22, 2019 #WEB Live-Webinar “Orientierung im Big Data Dschungel” mit Inga Ketels
• Mar 20, 2019 #WEB Insights and Innovation Webinar Series: #3 Big Data for a Better Built Environment

More WEB events? Click Here

[ AnalyticsWeek BYTES]

>> Data Science is more than Machine Learning  by analyticsweek

>> The Upper Echelons of Cognitive Computing: Deriving Business Value from Speech Recognition by jelaniharper

>> Talend and Splunk: Aggregate, Analyze and Get Answers from Your Data Integration Jobs by analyticsweekpick

Wanna write? Click Here

[ NEWS BYTES]

>>
 Regulating the Internet of Things – RFID Journal Under  Internet Of Things

>>
 Analytics Use Grows in Parallel with Data Volumes – Datanami Under  Analytics

>>
 Startup right in 2019: how to set up your customer experience for success – SmartCompany.com.au Under  Customer Experience

More NEWS ? Click Here

[ FEATURED COURSE]

Process Mining: Data science in Action

Process mining is the missing link between model-based process analysis and data-oriented analysis techniques. Through concrete data sets and easy to use software the course provides data science knowledge that can be ap… more

[ FEATURED READ]

Introduction to Graph Theory (Dover Books on Mathematics)

A stimulating excursion into pure mathematics aimed at “the mathematically traumatized,” but great fun for mathematical hobbyists and serious mathematicians as well. Requiring only high school algebra as mathematical bac… more

[ TIPS & TRICKS OF THE WEEK]

Save yourself from zombie apocalypse from unscalable models
One living and breathing zombie in today’s analytical models is the pulsating absence of error bars. Not every model is scalable or holds ground with increasing data. Error bars that is tagged to almost every models should be duly calibrated. As business models rake in more data the error bars keep it sensible and in check. If error bars are not accounted for, we will make our models susceptible to failure leading us to halloween that we never wants to see.

[ DATA SCIENCE Q&A]

Q:You are compiling a report for user content uploaded every month and notice a spike in uploads in October. In particular, a spike in picture uploads. What might you think is the cause of this, and how would you test it?
A: * Halloween pictures?
* Look at uploads in countries that don’t observe Halloween as a sort of counter-factual analysis
* Compare uploads mean in October and uploads means with September: hypothesis testing

Source

[ VIDEO OF THE WEEK]

 @AnalyticsWeek #FutureOfData with Robin Thottungal(@rathottungal), Chief Data Scientist at @EPA

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[ QUOTE OF THE WEEK]

It is a capital mistake to theorize before one has data. Insensibly, one begins to twist the facts to suit theories, instead of theories to

[ PODCAST OF THE WEEK]

 #BigData @AnalyticsWeek #FutureOfData #Podcast with Dr. Nipa Basu, @DnBUS

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[ FACT OF THE WEEK]

Retailers who leverage the full power of big data could increase their operating margins by as much as 60%.

Sourced from: Analytics.CLUB #WEB Newsletter

[  COVER OF THE WEEK ]

Accuracy check  Source

[ LOCAL EVENTS & SESSIONS]

• Feb 06, 2019 #WEB Online Meetup: Best Practices for Kubernetes
• Mar 07, 2019 #WEB Combining GIS and Statistics: Data Visualization to Communicate Findings
• Feb 07, 2019 #WEB Big Data Hadoop & Spark Bootcamp – Learn in a fun way

More WEB events? Click Here

[ AnalyticsWeek BYTES]

>> January 30, 2017 Health and Biotech analytics news roundup by pstein

>> Oct 18, 18: #AnalyticsClub #Newsletter (Events, Tips, News & more..) by admin

>> How will social media analytics bring your business closer to success? by thomassujain

Wanna write? Click Here

[ NEWS BYTES]

>>
 8 common questions from aspiring data scientists, answered – Tech in Asia Under  Data Scientist

>>
 D-Link Camera Poses Data Security Risk, Consumer Reports Finds … – ConsumerReports.org Under  Data Security

>>
 Cyber Security – KSNF/KODE – FourStatesHomepage.com Under  cyber security

More NEWS ? Click Here

[ FEATURED COURSE]

Process Mining: Data science in Action

Process mining is the missing link between model-based process analysis and data-oriented analysis techniques. Through concrete data sets and easy to use software the course provides data science knowledge that can be ap… more

[ FEATURED READ]

The Signal and the Noise: Why So Many Predictions Fail–but Some Don’t

People love statistics. Statistics, however, do not always love them back. The Signal and the Noise, Nate Silver’s brilliant and elegant tour of the modern science-slash-art of forecasting, shows what happens when Big Da… more

[ TIPS & TRICKS OF THE WEEK]

Strong business case could save your project
Like anything in corporate culture, the project is oftentimes about the business, not the technology. With data analysis, the same type of thinking goes. It’s not always about the technicality but about the business implications. Data science project success criteria should include project management success criteria as well. This will ensure smooth adoption, easy buy-ins, room for wins and co-operating stakeholders. So, a good data scientist should also possess some qualities of a good project manager.

[ DATA SCIENCE Q&A]

Q:Give examples of bad and good visualizations?
A: Bad visualization:
– Pie charts: difficult to make comparisons between items when area is used, especially when there are lots of items
– Color choice for classes: abundant use of red, orange and blue. Readers can think that the colors could mean good (blue) versus bad (orange and red) whereas these are just associated with a specific segment
– 3D charts: can distort perception and therefore skew data
– Using a solid line in a line chart: dashed and dotted lines can be distracting

Good visualization:
– Heat map with a single color: some colors stand out more than others, giving more weight to that data. A single color with varying shades show the intensity better
– Adding a trend line (regression line) to a scatter plot help the reader highlighting trends

Source

[ VIDEO OF THE WEEK]

 @AnalyticsWeek Keynote: The CMO isn’t satisfied: Judah Phillips

Subscribe to  Youtube

[ QUOTE OF THE WEEK]

I’m sure, the highest capacity of storage device, will not enough to record all our stories; because, everytime with you is very valuable da

[ PODCAST OF THE WEEK]

 #BigData @AnalyticsWeek #FutureOfData #Podcast with @MPFlowersNYC, @enigma_data

Subscribe 

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[ FACT OF THE WEEK]

100 terabytes of data uploaded daily to Facebook.

Sourced from: Analytics.CLUB #WEB Newsletter

[  COVER OF THE WEEK ]

Data Storage  Source

[ LOCAL EVENTS & SESSIONS]

• Feb 20, 2019 #WEB Data Science in 30 Minutes: Infonomics, The New Economics of Information with Gartner’s Doug Laney
• Jan 28, 2019 #WEB SAP FICO Certification Training in Houston, TX
• Jan 25, 2019 #WEB Azure Security – Protecting Your Environment with Tim Radney

More WEB events? Click Here

[ AnalyticsWeek BYTES]

>> Big Data Analytics, Supercomputing Seed Growth in Plant Research by analyticsweekpick

>> August 14, 2017 Health and Biotech analytics news roundup by pstein

>> Refugee migration: Where are people fleeing from and where are they going? by analyticsweek

Wanna write? Click Here

[ NEWS BYTES]

>>
 Prescriptive and Predictive Analytics Market Will Boast Developments in Global Industry by 2018-2025 – Leading Journal (blog) Under  Talent Analytics

>>
 Machine-learning algorithm predicts how cells repair broken DNA – EurekAlert (press release) Under  Machine Learning

>>
 200 jobs in Belfast being created by US cyber security firm – RTE.ie Under  cyber security

More NEWS ? Click Here

[ FEATURED COURSE]

Machine Learning

6.867 is an introductory course on machine learning which gives an overview of many concepts, techniques, and algorithms in machine learning, beginning with topics such as classification and linear regression and ending … more

[ FEATURED READ]

Storytelling with Data: A Data Visualization Guide for Business Professionals

Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You’ll discover the power of storytelling and the way to make data a pivotal point in your story. Th… more

[ TIPS & TRICKS OF THE WEEK]

Keeping Biases Checked during the last mile of decision making
Today a data driven leader, a data scientist or a data driven expert is always put to test by helping his team solve a problem using his skills and expertise. Believe it or not but a part of that decision tree is derived from the intuition that adds a bias in our judgement that makes the suggestions tainted. Most skilled professionals do understand and handle the biases well, but in few cases, we give into tiny traps and could find ourselves trapped in those biases which impairs the judgement. So, it is important that we keep the intuition bias in check when working on a data problem.

[ DATA SCIENCE Q&A]

Q:Is it better to spend 5 days developing a 90% accurate solution, or 10 days for 100% accuracy? Depends on the context?
A: * “premature optimization is the root of all evils”
* At the beginning: quick-and-dirty model is better
* Optimization later
Other answer:
– Depends on the context
– Is error acceptable? Fraud detection, quality assurance

Source

[ VIDEO OF THE WEEK]

 #BigData @AnalyticsWeek #FutureOfData #Podcast with Eloy Sasot, News Corp

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[ QUOTE OF THE WEEK]

Big Data is not the new oil. – Jer Thorp

[ PODCAST OF THE WEEK]

 @JohnTLangton from @Wolters_Kluwer discussed his #AI Lead Startup Journey #FutureOfData #Podcast

Subscribe 

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[ FACT OF THE WEEK]

Facebook stores, accesses, and analyzes 30+ Petabytes of user generated data.

Sourced from: Analytics.CLUB #WEB Newsletter

[  COVER OF THE WEEK ]

SQL Database  Source

[ LOCAL EVENTS & SESSIONS]

• Feb 20, 2019 #WEB Data Science in 30 Minutes: Infonomics, The New Economics of Information with Gartner’s Doug Laney
• Feb 07, 2019 #WEB Develop a Successful Cybersecurity Tech Entrepreneur Startup Business Today! Houston – Entrepreneur – Workshop – Hackathon – Bootcamp – Virtual Class – Seminar – Training – Lecture – Webinar – Conference – Course
• Feb 16, 2019 #WEB Artificial Intelligence – AI on Microsoft Platform

More WEB events? Click Here

[ AnalyticsWeek BYTES]

>> Improving the Customer Experience Through Big Data [VIDEO] by bobehayes

>> Accelerating Discovery with a Unified Analytics Platform for Genomics by analyticsweek

>> The UX of Brokerage Websites by analyticsweek

Wanna write? Click Here

[ NEWS BYTES]

>>
 Italy-America Chamber, Luxury Marketing Council host 2nd Annual Luxury Summit – Luxury Daily Under  Social Analytics

>>
 Top five business analytics intelligence trends for 2019 – Information Age Under  Analytics

>>
 Billions of dollars have not helped Indian e-tailers figure out AI and big data – Quartz Under  Big Data Analytics

More NEWS ? Click Here

[ FEATURED COURSE]

Artificial Intelligence

This course includes interactive demonstrations which are intended to stimulate interest and to help students gain intuition about how artificial intelligence methods work under a variety of circumstances…. more

[ FEATURED READ]

The Industries of the Future

The New York Times bestseller, from leading innovation expert Alec Ross, a “fascinating vision” (Forbes) of what’s next for the world and how to navigate the changes the future will bring…. more

[ TIPS & TRICKS OF THE WEEK]

Winter is coming, warm your Analytics Club
Yes and yes! As we are heading into winter what better way but to talk about our increasing dependence on data analytics to help with our decision making. Data and analytics driven decision making is rapidly sneaking its way into our core corporate DNA and we are not churning practice ground to test those models fast enough. Such snugly looking models have hidden nails which could induce unchartered pain if go unchecked. This is the right time to start thinking about putting Analytics Club[Data Analytics CoE] in your work place to help Lab out the best practices and provide test environment for those models.

[ DATA SCIENCE Q&A]

Q:Why is naive Bayes so bad? How would you improve a spam detection algorithm that uses naive Bayes?
A: Naïve: the features are assumed independent/uncorrelated
Assumption not feasible in many cases
Improvement: decorrelate features (covariance matrix into identity matrix)

Source

[ VIDEO OF THE WEEK]

 @JustinBorgman on Running a data science startup, one decision at a time #Futureofdata #Podcast

Subscribe to  Youtube

[ QUOTE OF THE WEEK]

Data beats emotions. – Sean Rad, founder of Ad.ly

[ PODCAST OF THE WEEK]

 @JustinBorgman on Running a data science startup, one decision at a time #Futureofdata #Podcast

Subscribe 

iTunes  GooglePlay

[ FACT OF THE WEEK]

73% of organizations have already invested or plan to invest in big data by 2016

Sourced from: Analytics.CLUB #WEB Newsletter

[  COVER OF THE WEEK ]

Conditional Risk  Source

[ LOCAL EVENTS & SESSIONS]

• Jan 06, 2019 #WEB Free Webinar on Big Data with Scala & Spark – Live Instructor Led Session | Limited Seats | Arlington, TX
• Jan 06, 2019 #WEB Free Webinar on Big Data with Scala & Spark – Live Instructor Led Session | Limited Seats | Houston, TX
• Jan 18, 2019 #WEB Webinar-Flatrate 2019 – Lunch & Learn

More WEB events? Click Here

[ AnalyticsWeek BYTES]

>> Looking out for Big Data Capital of the World by v1shal

>> It’s Official! Talend to Welcome Stitch to the Family! by analyticsweekpick

>> Data Management Rules for Analytics by analyticsweek

Wanna write? Click Here

[ NEWS BYTES]

>>
 Startups aspiring to market like big brands: with Smartech & AI, today they can – YourStory.com Under  Prescriptive Analytics

>>
 Ecolab Inc (NYSE:ECL) Institutional Investor Sentiment Analysis – The Cardinal Weekly (press release) Under  Sentiment Analysis

>>
 Data center outsourcing faces a legal test – DatacenterDynamics Under  Data Center

More NEWS ? Click Here

[ FEATURED COURSE]

Python for Beginners with Examples

A practical Python course for beginners with examples and exercises…. more

[ FEATURED READ]

The Black Swan: The Impact of the Highly Improbable

A black swan is an event, positive or negative, that is deemed improbable yet causes massive consequences. In this groundbreaking and prophetic book, Taleb shows in a playful way that Black Swan events explain almost eve… more

[ TIPS & TRICKS OF THE WEEK]

Grow at the speed of collaboration
A research by Cornerstone On Demand pointed out the need for better collaboration within workforce, and data analytics domain is no different. A rapidly changing and growing industry like data analytics is very difficult to catchup by isolated workforce. A good collaborative work-environment facilitate better flow of ideas, improved team dynamics, rapid learning, and increasing ability to cut through the noise. So, embrace collaborative team dynamics.

[ DATA SCIENCE Q&A]

Q:How do you test whether a new credit risk scoring model works?
A: * Test on a holdout set
* Kolmogorov-Smirnov test

Kolmogorov-Smirnov test:
– Non-parametric test
– Compare a sample with a reference probability distribution or compare two samples
– Quantifies a distance between the empirical distribution function of the sample and the cumulative distribution function of the reference distribution
– Or between the empirical distribution functions of two samples
– Null hypothesis (two-samples test): samples are drawn from the same distribution
– Can be modified as a goodness of fit test
– In our case: cumulative percentages of good, cumulative percentages of bad

Source

[ VIDEO OF THE WEEK]

 Data-As-A-Service (#DAAS) to enable compliance reporting

Subscribe to  Youtube

[ QUOTE OF THE WEEK]

You can have data without information, but you cannot have information without data. – Daniel Keys Moran

[ PODCAST OF THE WEEK]

 Solving #FutureOfOrgs with #Detonate mindset (by @steven_goldbach & @geofftuff) #FutureOfData #Podcast

Subscribe 

iTunes  GooglePlay

[ FACT OF THE WEEK]

2.7 Zetabytes of data exist in the digital universe today.

Sourced from: Analytics.CLUB #WEB Newsletter

[  COVER OF THE WEEK ]

Data shortage  Source

[ LOCAL EVENTS & SESSIONS]

• Jan 19, 2019 #WEB Diploma in Data Sciences – Real Time OnLine Weekend Program Started -First Batch
• Jan 15, 2019 #WEB Thinkful Online Info Session | Becoming a Data Scientist
• Jan 24, 2019 #WEB Webinar: A Buyer’s Journey in SaaS World by DELL Principal PM

More WEB events? Click Here

[ AnalyticsWeek BYTES]

>> Large Visualizations in canvasXpress by analyticsweek

>> How to pick the right sample for your analysis by jburchell

>> How Google Understands You [Infographic] by v1shal

Wanna write? Click Here

[ NEWS BYTES]

>>
 Meet data center compliance standards in hybrid deployments – TechTarget Under  Data Center

>>
 Approaching The Hybrid Cloud Computing Model For Modern Government – Forbes Under  Cloud

>>
 Financial Analytics Market 2018 Report with Manufacturers, Dealers, Consumers, Revenue, Regions, Types, Application – The Iowa DeltaChi Under  Financial Analytics

More NEWS ? Click Here

[ FEATURED COURSE]

Introduction to Apache Spark

Learn the fundamentals and architecture of Apache Spark, the leading cluster-computing framework among professionals…. more

[ FEATURED READ]

Rise of the Robots: Technology and the Threat of a Jobless Future

What are the jobs of the future? How many will there be? And who will have them? As technology continues to accelerate and machines begin taking care of themselves, fewer people will be necessary. Artificial intelligence… more

[ TIPS & TRICKS OF THE WEEK]

Keeping Biases Checked during the last mile of decision making
Today a data driven leader, a data scientist or a data driven expert is always put to test by helping his team solve a problem using his skills and expertise. Believe it or not but a part of that decision tree is derived from the intuition that adds a bias in our judgement that makes the suggestions tainted. Most skilled professionals do understand and handle the biases well, but in few cases, we give into tiny traps and could find ourselves trapped in those biases which impairs the judgement. So, it is important that we keep the intuition bias in check when working on a data problem.

[ DATA SCIENCE Q&A]

Q:How do you assess the statistical significance of an insight?
A: * is this insight just observed by chance or is it a real insight?
Statistical significance can be accessed using hypothesis testing:
– Stating a null hypothesis which is usually the opposite of what we wish to test (classifiers A and B perform equivalently, Treatment A is equal of treatment B)
– Then, we choose a suitable statistical test and statistics used to reject the null hypothesis
– Also, we choose a critical region for the statistics to lie in that is extreme enough for the null hypothesis to be rejected (p-value)
– We calculate the observed test statistics from the data and check whether it lies in the critical region

Common tests:
– One sample Z test
– Two-sample Z test
– One sample t-test
– paired t-test
– Two sample pooled equal variances t-test
– Two sample unpooled unequal variances t-test and unequal sample sizes (Welch’s t-test)
– Chi-squared test for variances
– Chi-squared test for goodness of fit
– Anova (for instance: are the two regression models equals? F-test)
– Regression F-test (i.e: is at least one of the predictor useful in predicting the response?)

Source

[ VIDEO OF THE WEEK]

 #FutureOfData with Rob(@telerob) / @ConnellyAgency on running innovation in agency

Subscribe to  Youtube

[ QUOTE OF THE WEEK]

War is 90% information. – Napoleon Bonaparte

[ PODCAST OF THE WEEK]

 Scott Harrison (@SRHarrisonJD) on leading the learning organization #JobsOfFuture #Podcast

Subscribe 

iTunes  GooglePlay

[ FACT OF THE WEEK]

Estimates suggest that by better integrating big data, healthcare could save as much as $300 billion a year — that’s equal to reducing costs by $1000 a year for every man, woman, and child.

Sourced from: Analytics.CLUB #WEB Newsletter

[  COVER OF THE WEEK ]

Ethics  Source

[ LOCAL EVENTS & SESSIONS]

• Jan 24, 2019 #WEB Webinar: A Buyer’s Journey in SaaS World by DELL Principal PM
• Jan 06, 2019 #WEB Free Webinar on Big Data with Scala & Spark – Live Instructor Led Session | Limited Seats | Amsterdam, Netherlands
• Jan 06, 2019 #WEB Free Webinar on Big Data with Scala & Spark – Live Instructor Led Session | Limited Seats | Newark, NJ

More WEB events? Click Here

[ AnalyticsWeek BYTES]

>> Is the Importance of Customer Experience Overinflated? by bobehayes

>> The End of Transformation: Expediting Data Preparation and Analytics with Edge Computing by jelaniharper

>> The Pitfalls of Using Predictive Models by bobehayes

Wanna write? Click Here

[ NEWS BYTES]

>>
 The Transformation of Healthcare with AI and Machine Learning – InformationWeek Under  Machine Learning

>>
 Let’s Make Artificial Intelligence ‘Boring’ Again – Forbes Under  Artificial Intelligence

>>
 Verint Systems Inc. (VRNT) Holdings Cut by Harel Insurance Investments & Financial Services Ltd. – Fairfield Current Under  Social Analytics

More NEWS ? Click Here

[ FEATURED COURSE]

R, ggplot, and Simple Linear Regression

Begin to use R and ggplot while learning the basics of linear regression… more

[ FEATURED READ]

The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World

In the world’s top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask. In The Mast… more

[ TIPS & TRICKS OF THE WEEK]

Data Analytics Success Starts with Empowerment
Being Data Driven is not as much of a tech challenge as it is an adoption challenge. Adoption has it’s root in cultural DNA of any organization. Great data driven organizations rungs the data driven culture into the corporate DNA. A culture of connection, interactions, sharing and collaboration is what it takes to be data driven. Its about being empowered more than its about being educated.

[ DATA SCIENCE Q&A]

Q:Explain selection bias (with regard to a dataset, not variable selection). Why is it important? How can data management procedures such as missing data handling make it worse?
A: * Selection of individuals, groups or data for analysis in such a way that proper randomization is not achieved
Types:
– Sampling bias: systematic error due to a non-random sample of a population causing some members to be less likely to be included than others
– Time interval: a trial may terminated early at an extreme value (ethical reasons), but the extreme value is likely to be reached by the variable with the largest variance, even if all the variables have similar means
– Data: “cherry picking”, when specific subsets of the data are chosen to support a conclusion (citing examples of plane crashes as evidence of airline flight being unsafe, while the far more common example of flights that complete safely)
– Studies: performing experiments and reporting only the most favorable results
– Can lead to unaccurate or even erroneous conclusions
– Statistical methods can generally not overcome it

Why data handling make it worse?
– Example: individuals who know or suspect that they are HIV positive are less likely to participate in HIV surveys
– Missing data handling will increase this effect as it’s based on most HIV negative
-Prevalence estimates will be unaccurate

Source

[ VIDEO OF THE WEEK]

 Making sense of unstructured data by turning strings into things

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[ QUOTE OF THE WEEK]

What we have is a data glut. – Vernon Vinge

[ PODCAST OF THE WEEK]

 #FutureOfData with @theClaymethod, @TiVo discussing running analytics in media industry

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[ FACT OF THE WEEK]

Every second we create new data. For example, we perform 40,000 search queries every second (on Google alone), which makes it 3.5 searches per day and 1.2 trillion searches per year.In Aug 2015, over 1 billion people used Facebook FB +0.54% in a single day.

Sourced from: Analytics.CLUB #WEB Newsletter

[  COVER OF THE WEEK ]

Trust the data  Source

[ LOCAL EVENTS & SESSIONS]

• Jan 07, 2019 #WEB Data Science Essentials Training & Internship
• Jan 06, 2019 #WEB Free Webinar on Big Data with Scala & Spark – Live Instructor Led Session | Limited Seats | Seattle, WA
• Jan 24, 2019 #WEB Webinar: A Buyer’s Journey in SaaS World by DELL Principal PM

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[ AnalyticsWeek BYTES]

>> Big Data Integration and Your Customer Genome by bobehayes

>> New Study: Top 3 Trends in Embedded Analytics by analyticsweek

>> Big Data Will Keep the Shale Boom Rolling by analyticsweekpick

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[ NEWS BYTES]

>>
 Streaming Analytics: How to Realize Its Full Potential – RTInsights (press release) (blog) Under  Streaming Analytics

>>
 Lenovo launches ThinkShield for data security – The Hindu BusinessLine Under  Data Security

>>
 Digital Trust model, cloud-based security to drive cyber security in 2019 – The Hindu BusinessLine Under  cyber security

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[ FEATURED COURSE]

Introduction to Apache Spark

Learn the fundamentals and architecture of Apache Spark, the leading cluster-computing framework among professionals…. more

[ FEATURED READ]

Superintelligence: Paths, Dangers, Strategies

The human brain has some capabilities that the brains of other animals lack. It is to these distinctive capabilities that our species owes its dominant position. Other animals have stronger muscles or sharper claws, but … more

[ TIPS & TRICKS OF THE WEEK]

Grow at the speed of collaboration
A research by Cornerstone On Demand pointed out the need for better collaboration within workforce, and data analytics domain is no different. A rapidly changing and growing industry like data analytics is very difficult to catchup by isolated workforce. A good collaborative work-environment facilitate better flow of ideas, improved team dynamics, rapid learning, and increasing ability to cut through the noise. So, embrace collaborative team dynamics.

[ DATA SCIENCE Q&A]

Q:Give examples of data that does not have a Gaussian distribution, nor log-normal?
A: * Allocation of wealth among individuals
* Values of oil reserves among oil fields (many small ones, a small number of large ones)

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[ VIDEO OF THE WEEK]

 Using Topological Data Analysis on your BigData

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[ QUOTE OF THE WEEK]

War is 90% information. – Napoleon Bonaparte

[ PODCAST OF THE WEEK]

 Scott Harrison (@SRHarrisonJD) on leading the learning organization #JobsOfFuture #Podcast

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[ FACT OF THE WEEK]

In 2015, a staggering 1 trillion photos will be taken and billions of them will be shared online. By 2017, nearly 80% of photos will be taken on smart phones.

Sourced from: Analytics.CLUB #WEB Newsletter