In this brief retrospective episode, Shane, Alcine and their 'Magic Millennial' producer, Maya Cueva look back at Season 1, reflecting on the moments that nested deepest in their hearts. You’ll get to hear or revisit impactful clips from guests in Season 1 and hear about what our producer Maya Cueva is up to on her other projects. The hosts also talk about current innovations from outside of education, including sobriety “quit lit” and Dr. Gabor Maté’s incredible work on childhood development, trauma and the potential lifelong impacts on physical and mental health conditions that show up daily in our schools and classrooms. As we prepare to launch Season 2 in February, Alcine invokes Dr. Jamila Dugan’s invitation in Episode 4: “How do I dream bigger and in community? Who do I need to be in community with so that my dreams become bigger?” Join us and dream with us about next-generation schools that affirm love and value every child!

For Further Learning:

Learn about Producer Maya Cueva’s PBS project On the Divide Host a screening of On The Divide vía GOOD Docs! https://gooddocs.net/products/on-the-divide  Episodes mentioned and excerpted include: https://www.onthedividemovie.com 

Episode 4: “What Does it Mean to Freedom Dream?”: Disrupting Traps and Tropes with Dr. Jamila Dugan

Episode 6: “We Need to Marginalize Standardized Testing” with Young Whan Choi

Episode 8: “Connecting Present to Past”: The Impact of Critical Pedagogy with Rocky Rivera and Norma Gallegos

If you’re interested in listening to Tales of The Town, the podcast about Oakland — listen here. You can also get tickets to the Tales of The Town film: https://www.talesofthetown.info Tales of the Town Podcast : https://podcasts.apple.com/us/podcast/introducing-tales-of-the-town-a-podcast-about-black-oakland/id1235932328?i=1000579592977  Get Dr. Gholdy Mohammed’s Cultivating Genius

We talked about

Chris’s background Switching careers multiple times Freedom at companies Chris’s role as an internal consultant Chris’s sabbatical ChatGPT How being a generalist helped Chris in his career The cons of being a generalist and the importance of T-shaped expertise The importance of learning things you’re interested in Tips to enjoy learning new things Recruiting generalists The job market for generalists vs for specialists Narrowing down your interests Chris’s book recommendations

Links:

Lex Fridman: science, philosophy, media, AI (especially earlier episodes): https://www.youtube.com/lexfridman Andrej Karpathy, former Senior Director of AI at Tesla, who's now focused on teaching and sharing his knowledge: https://www.youtube.com/@AndrejKarpathy Beautifully done videos on engineering of things in the real world: https://www.youtube.com/@RealEngineering Chris' website: https://szafranek.net/ Zalando Tech Radar: https://opensource.zalando.com/tech-radar/ Modal Labs, new way of deploying code to the cloud, also useful for testing ML code on GPUs: https://modal.com Excellent Twitter account to follow to learn more about prompt engineering for ChatGPT: https://twitter.com/goodside Image prompts for Midjourney: https://twitter.com/GuyP Machine Learning Workflows in Production - Krzysztof Szafanek: https://www.youtube.com/watch?v=CO4Gqd95j6k From Data Science to DataOps: https://datatalks.club/podcast/s11e03-from-data-science-to-dataops.html

Free data engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp

Join DataTalks.Club: https://datatalks.club/slack.html

Our events: https://datatalks.club/events.html

We talked about:

David’s background A day in the life of a professor David’s current projects Starting a school The different types of professors David’s recent papers Similarities and differences between research labs and startups Finding (or creating) good datasets David’s lab Balancing research and teaching as a professor David’s most rewarding research project David’s most underrated research project David’s virtual data science seminars on YouTube Teaching at universities without doing research Staying up-to-date in research David’s favorite conferences Selecting topics for research Convincing students to stay in academia and competing with industry Finding David online

Links: 

David A. Bader: https://davidbader.net/ NJIT Institute for Data Science: https://datascience.njit.edu/ Arkouda: https://github.com/Bears-R-Us/arkouda NJIT Data Science YouTube Channel: https://www.youtube.com/c/NJITInstituteforDataScience

ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp

Join DataTalks.Club: https://datatalks.club/slack.html

Our events: https://datatalks.club/events.html

We talked about:

Christiaan’s background Usual ways of collecting and curating data Getting the buy-in from experts and executives Starting an annotation booklet Pre-labeling Dataset collection Human level baseline and feedback Using the annotation booklet to boost annotation productivity Putting yourself in the shoes of annotators (and measuring performance) Active learning Distance supervision Weak labeling Dataset collection in career positioning and project portfolios IPython widgets GDPR compliance and non-English NLP Finding Christiaan online

Links:

My personal blog: https://useml.net/ Comtura, my company: https://comtura.ai/ LI: https://www.linkedin.com/in/christiaan-swart-51a68967/ Twitter: https://twitter.com/swartchris8/

ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp

Join DataTalks.Club: https://datatalks.club/slack.html

Our events: https://datatalks.club/events.html

In this episode, Bryce and Conor interview Kate Gregory about her career history. Link to Episode 92 on Website Twitter ADSP: The PodcastConor HoekstraBryce Adelstein LelbachAbout the Guest: Kate Gregory is an author, sought-after conference speaker, trainer, Microsoft Most Valuable Professional (MVP), and partner at Gregory Consulting. Kate has been using C++ since before Microsoft had a C++ compiler. She is an early adopter of many software technologies and tools, and a well-connected member of the software development community. Kate is one of the founders of #include whose goal is a more welcoming and inclusive C++ community. She also serves on the board of directors of Cpp Toronto, a non-profit organization that provides an open, inclusive, and collaborative place where software developers can meet and discuss topics related to C++ software development. Show Notes Date Recorded: 2022-08-15 Date Released: 2022-08-26 Podcast Appearances CppCast Episode 30: Stop Teaching C (When Teaching C++)Episode 148: C++ SimplicityEpisode 238: Beautiful C++.NET Rocks! Episode 88: Kate Gregory on C+++, VB.NET, and VSTOOther .Net Rocks Episodes (search “Kate Gregory”)CoRecursive Episode 56: Memento Mori With Kate GregoryOther Links C++Now 2019: Conor Hoekstra “Algorithm Intuition”CppCon 2015: Kate Gregory “Stop Teaching C”Keynote: “Am I A Good Programmer?” - Kate Gregory - CppNorth 2022Beautiful C++: 30 Core Guidelines for Writing Clean, Safe, and Fast Code by Guy Davidson & Kate GregoryWATFOR — The University of Waterloo FORTRAN IV compilerWATFIVPluralSight - Kate GregoryNDC TechTown - Magazinet Kongsberg (29 Aug – 1 Sept)Intro Song Info Miss You by Sarah Jansen https://soundcloud.com/sarahjansenmusic Creative Commons — Attribution 3.0 Unported — CC BY 3.0 Free Download / Stream: http://bit.ly/l-miss-you Music promoted by Audio Library https://youtu.be/iYYxnasvfx8

We talked about:

DataTalks.Club intro Tereza’s background Working as a coach Identifying the mismatches between your needs and that of a company How to avoid misalignments Considering what’s mentioned in the job description, what isn’t, and why Diversity and culture of a company Lack of a salary in the job description Way of doing research about the company where you will potentially work How to avoid a mismatch with a company other than learning from your mistakes Before data, during data, after data (a company’s data maturity level) The company’s tech stack Finding Tereza online

Links: 

Decoding Data Science Job Descriptions (talk): https://www.youtube.com/watch?v=WAs9vSNTza8 Talk at ConnectForward: https://www.youtube.com/watch?v=WAs9vSNTza8 Slides: https://www.slideshare.net/terezaif/decoding-data-science-job-descriptions-250687704 Talk at DataLift: https://www.youtube.com/watch?v=pCtQ0szJiLA Slides: https://www.slideshare.net/terezaif/lessons-learned-from-hiring-and-retaining-data-practitioners

MLOps Zoomcamp: https://github.com/DataTalksClub/mlops-zoomcamp

Join DataTalks.Club: https://datatalks.club/slack.html

Our events: https://datatalks.club/events.html

We talked about:

Daynan’s background Astronomy vs cosmology Applications of data science and machine learning in astronomy Determining signal vs noise What the data looks like in astronomy Determining the features of an object in space Ground truth for space objects Why water is an important resource in the space economy Other useful resources that can be found in asteroids Sources of asteroids The data team at an asteroid mining company Open datasets for hobbyists Mission and hardware design for asteroid mining Partnerships and hires

Links: 

LinkedIn: https://www.linkedin.com/in/daynan/ We're looking for a Sr Data Engineer: https://boards.eu.greenhouse.io/karmanplus/jobs/4027128101?gh_jid=4027128101 Minor Planet Center: https://minorplanetcenter.net/- JPL Horizons has a nice set of APIs for accessing data related to small bodies (including asteroids): https://ssd.jpl.nasa.gov/api.html ESA has NEODyS: https://newton.spacedys.com/neodys   IRSA catalog that contains image and catalog data related to the WISE/NEOWISE data (and other infrared platforms): https://irsa.ipac.caltech.edu/frontpage/ NASA also has an archive of data collected from their various missions, including a node related to small bodies: https://pds-smallbodies.astro.umd.edu/ Sub-node directly related to asteroids: https://sbn.psi.edu/pds/ Size, Mass, and Density of Asteroids (SiMDA) is a nice catalog of observed asteroid attributes (and an indication of how small our sample size is!): https://astro.kretlow.de/?SiMDA The source survey data, several are useful for asteroids: Pan-STARRS (https://outerspace.stsci.edu/display/PANSTARRS)

MLOps Zoomcamp: https://github.com/DataTalksClub/mlops-zoomcamp

Join DataTalks.Club: https://datatalks.club/slack.html

Our events: https://datatalks.club/events.html

Thanks for tuning in to the Data Driven Strength Podcast!

Timestamps:

01:04 New review paper on the limitations of proximity to failure research

13:50 What is the effect size of interest?

41:00 Strength Limiter Discussion

To learn more about 1 on 1 coaching: https://datadrivenstrength.typeform.com/to/JR3Gzm?typeform-source=linktr.ee

If you'd like to sign up to our email list, please visit the bottom section of our website via this link:

https://www.data-drivenstrength.com

If you’d like to submit a question for a future episode please follow the link provided:

https://forms.gle/c5aCswfCq6XUDTiAA

Link to Individualized Programming + Self Coaching Toolkit Product Page:

https://www.data-drivenstrength.com/individualized-programming Links to papers discussed:

1. https://www.researchgate.net/publication/359044527_Methods_for_Controlling_and_Reporting_Resistance_Training_Proximity_to_Failure_Current_Issues_and_Future_Directions

2. https://pubmed.ncbi.nlm.nih.gov/35263685/

3. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7725035/

4. https://journals.lww.com/nsca-jscr/Fulltext/2021/02001/Impact_of_Two_High_Volume_Set_Configuration.21.aspx?fbclid=IwAR3_TzZaaPIK6ZaoK5Tty3e22GgJU_1sJMtdHICV1Okq0AQSVfqvwdNu1fM

Follow us on Instagram at: @datadrivenstrength @zac.datadrivenstrength @josh.datadrivenstrength @jake.datadrivenstrength @drake.datadrivenstrength

Thanks for tuning in to the Data Driven Strength Podcast!

Timestamps: 

00:00 Intro/general update 

10:02 Home gym equipment and setting up weighted pushups 

23:47 Training frequency and proximity to failure 

36:14 Rate of force development discussion 

01:09:00 Minimum effective dose for strength and hypertrophy    

To learn more about 1 on 1 coaching: https://datadrivenstrength.typeform.com/to/JR3Gzm?typeform-source=linktr.ee 

If you'd like to sign up to our email list, please visit the bottom section of our website via this link: https://www.data-drivenstrength.com 

If you’d like to submit a question for a future episode please follow the link provided: https://forms.gle/c5aCswfCq6XUDTiAA 

Link to Individualized Programming + Self Coaching Toolkit Product Page: https://www.data-drivenstrength.com/individualized-programming 

Training to Failure Fatigue Meta discussed: 

1. https://link.springer.com/article/10.1007/s40279-021-01602-x 

Links to RFD papers discussed: 

1. https://onlinelibrary.wiley.com/doi/pdf/10.1111/sms.13775?casa_token=EkLP_ZxQKuEAAAAA:pZoYDR1zERHdyTDFJhdkxJByWY4POb2kilm1JQnhf2o4-K-wWGKwk_iPxKpYJPrIwXHfxUfC1eso4yI

2. https://link.springer.com/content/pdf/10.1007/s00421-016-3439-2.pdf

3. https://www.mdpi.com/2076-3417/11/1/45

4. https://www.tandfonline.com/doi/pdf/10.1080/02640414.2015.1119299?needAccess=true

5. https://europepmc.org/article/med/34100789

6. https://pubmed.ncbi.nlm.nih.gov/29577974/

7. https://www.researchgate.net/publication/325748706_Functional_and_physiological_adaptations_following_concurrent_training_using_sets_with_and_without_concentric_failure_in_elderly_men_A_randomized_clinical_trial

8. https://pubmed.ncbi.nlm.nih.gov/32049887/

9. https://journals.humankinetics.com/view/journals/ijspp/14/1/article-p46.xml 

Links to MED papers discussed: 

1. https://pubmed.ncbi.nlm.nih.gov/21131862/

2. https://www.frontiersin.org/articles/10.3389/fphys.2021.735932/full

3. https://pubmed.ncbi.nlm.nih.gov/31373973/ 

Follow us on Instagram at: @datadrivenstrength @zac.datadrivenstrength @josh.datadrivenstrength @jake.datadrivenstrength @drake.datadrivenstrength

Simson Garfinkel, Senior Computer Scientist for Confidentiality and Data Access at the US Census Bureau, discusses his work modernizing the Census Bureau disclosure avoidance system from private to public disclosure avoidance techniques using differential privacy. Some of the discussion revolves around the topics in the paper Randomness Concerns When Deploying Differential Privacy.   WORKS MENTIONED: "Calibrating Noise to Sensitivity in Private Data Analysis" by Cynthia Dwork, Frank McSherry, Kobbi Nissim, Adam Smith "Issues Encountered Deploying Differential Privacy" by Simson L Garfinkel, John M Abowd, and Sarah Powazek "Randomness Concerns When Deploying Differential Privacy" by Simson L. Garfinkel and Philip Leclerc 
Check out: https://simson.net/page/Differential_privacy

Thank you to our sponsor, BetterHelp. Professional and confidential in-app counseling for everyone. Save 10% on your first month of services with www.betterhelp.com/dataskeptic

Computer Science research fellow of Cambridge University, Heidi Howard discusses Paxos, Raft, and distributed consensus in distributed systems alongside with her work "Paxos vs. Raft: Have we reached consensus on distributed consensus?" She goes into detail about the leaders in Paxos and Raft and how The Raft Consensus Algorithm actually inspired her to pursue her PhD.

Paxos vs Raft paper: https://arxiv.org/abs/2004.05074

Leslie Lamport paper "part-time Parliament" https://lamport.azurewebsites.net/pubs/lamport-paxos.pdf

Leslie Lamport paper "Paxos Made Simple" https://lamport.azurewebsites.net/pubs/paxos-simple.pdf

Twitter : @heidiann360 Thank you to our sponsor Monday.com! Their apps challenge is still accepting submissions! find more information at monday.com/dataskeptic

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.  Abstract In this episode of Making Data Simple, we are joined with two very established members of the Informix user community. Art Kagel, President and Principal Consultant at ASK Database Management, and Lester Knutsen, President and Principal Database Consultant at Advanced DataTools Corporation. Together with host Al Martin, they touch on the state of the database and technology industry, sharing their wisdom of how far we have actually come. Tune in for a high-level discussion immersed in the world of data.  Connect with Art LinkedIn Twitter Connect with Lester LinkedIn Twitter Show Notes 03:38 - Here are the best diving sites in Indonesia, according to divezone.net. 20:15 - Check out this Globe News Wire article, predicting future growth for the enterprise data industry. 28:05 - Not sure what a five nines system is? Find out here. Connect with the Team Producer Liam Seston - LinkedIn. Producer Lana Cosic - LinkedIn. Producer Meighann Helene - LinkedIn.  Producer Mark Simmonds - LinkedIn.  Host Al Martin - LinkedIn and Twitter. Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Send us a text In an ever-changing and growing age of data and technology, how can you turn data into better decisions for your company? How do you keep up? Is there a recipe for greatness? In this podcast, Rob Thomas, General Manager of Analytics at IBM, discusses data, tech companies and his two books, Big Data Revolution and The End of Tech Companies.  "A crisis has arrived whether you know it or not." What are you doing to prepare? Show Notes 00:30 Connect with Al Martin on Twitter (@amartin_v) and LinkedIn (linkedin.com/in/al-martin-ku) 01:00  Connect with Rob Thomas on Twitter (@robdthomas) and LinkedIn (linkedin.com/in/robertdthomas) and read more of his work on his blog https://www.robdthomas.com/ 02:30 Big Data Revolution By Rob Thomas & Patrick McSharry, The End of Tech Companies by Rob Thomas 04:35 Find Rob Thomas' first blog post here: https://www.robdthomas.com/robdthomas//2013/02/patterns-in-big-data.html 05:30 Connect with Dr. Patrick E McSharry on LinkedIn linkedin.com/in/mcsharry, his personal website mcsharry.net or Twitter @patrickmcsharry 06:20 http://www.costar.com/ 14:10 Connect with Warren Buffett on Twitter (@WarrenBuffett) 14:40 Connect with Clayton Christensen on Twitter (@claychristensen) and LinkedIn (linkedin.com/in/claytonchristensen) 24:50 Learn More about DomusKids on their website http://domuskids.org/ and connect with them on Twitter @DomusKids 26:15 Above the Line: Lessons in Leadership and Life from a Championship Season by Urban Meyer & Wayne Coffey 26:30 Chasing Excellence: A Story About Building the World's Fittest Athletes by Ben Bergeron Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

HighlightsBerlin enjoyed some reggaetón and dance music on yesterday’s Shazam chartDJ/producer The Prince Karma recalls some Chainsmokers viral success in greater EuropeMissionGood morning, it’s Jason here at Chartmetric with your 3-minute Data Dump where we upload charts, artists and playlists into your brain so you can stay up on the latest in the music data world.DateThis is your Data Dump for Thursday April 11th 2019.Chart Highlight Let’s take a look at Berlin’s Shazam chart yesterday, which featured 50 tracks.It was a very pop-oriented list, with 18 “pop” genre tags leading as the most common and the “dance” genre tag coming in 2nd with 8 occurences.American singer-songwriter Ava Max was the only artist to have more than one track, with “So Am I” and “Sweet but Psycho” taking the #10 and #27 positions.Daddy Yankee’s “Con Calma feat. Snow” was the #1 most Shazamed track in Berlin, having been in their Top 50 for 48 days now with 3M Shazams total.The cheeky dance tune “Later Bitches” by The Prince Karma at Ultra Music took the #2 spot in Berlin. It was released back in May of last year and has a total of 5.2M Shazams globally.The #3 position was occupied by the Madism dance remix of “Someone You Loved” by Scotland’s Lewis Capaldi. That is its current peak position in Berlin and has a total of 1.5M Shazams.In terms of track age and time on chart, Berlin’s taste in music tends to be in middle of the road, as most of the chart is neither new or old, 27 of the tracks being anywhere from 1-6 months since release.And once they do make it to their city’s top 50, the tracks stay there for about the same amount of time, 1-6 months.Artist HighlightTracking back to the #2 position, the song “Later Bitches” has played out very well for DJ/producer The Prince Karma.There’s little information out on the Ultra Music label artist, but according to chartsinfrance.net, he is originally from Turkey and has been enjoying the success of his track since late last year.Somewhat similar to The Chainsmokers’ first hit “#SELFIE” in 2014, “Later Bitches” features a simple lead instrument hook, a four-on-the-floor kick drum beat, and funny spoken lines coming from an overzealous clubber like “what the hell do you mean I have to wait in line” and “I shouldn’t have had that last shot”.The Prince Karma has 1.7M Spotify monthly listeners and only 9K followers, giving him an astronomical listener to follower ratio of 197 that points towards an artist currently experiencing a viral hit. This ratio places him in the realm of no global superstars, but does put him in the company of likely other viral emerging artists such as acoustic UK songwriters Clementine Duo at a 197 ratio and Swedish singer-songwriter Plasi at 196.Mirroring his success on the Berlin Shazam chart, The Prince Karma is currently on the Top Hits Deutschland playlist on Spotify at 1.7M followers, while having been featured on Dance Party, Dance Rising and the Global Viral 50 playlists.The track also features on Apple Music’s Daily Top 100 Germany and Today’s Hits playlists in the German storefront, and the #73 position on the 7th most followed playlist on the Deezer platform, Orange Select.Probably the most interesting fact regarding the DJ’s only released track, the official YouTube video has 3.5M views since Sept 2018, but another video pre-dating the official one has 40.8M views, on a YouTube channel d2eTV (“Down to Earth”).Down2Earth Music Group is a multi-functional music company whose YouTube channel has an international presence, as the “Later Bitches” top comments section has comments in English, Polish, Russian and German...which makes sense as The Prince Karma has just finished up a Central & Eastern European tour.OutroThat’s it for your Daily Data Dump for Thursday April 11th 2019. This is Jason from Chartmetric.Feel free to sign up for a free account at chartmetric.io/signupAnd article links and show notes are at: chartmetric.transistor.fm/episodes.Happy Thursday, see you tomorrow. 

Master the basics of XML as well as the namespaces and objects you need to know in order to work efficiently with XML. You’ll learn extensive support for XML in everything from data access to configuration, from raw parsing to code documentation. You will see clear, practical examples that illustrate best practices in implementing XML APIs and services as part of your C#-based Windows 10 applications. Beginning XML with C# 7 is completely revised to cover the XML features of .NET Framework 4.7 using C# 7 programming language. In this update, you’ll discover the tight integration of XML with ADO.NET and LINQ as well as additional .NET support for today’s RESTful web services and Web API. Written by a Microsoft Most Valuable Professional and developer, this book demystifies everything to do with XML and C# 7. What You Will Learn: Discover how XML works with the .NET Framework Read, write, access, validate, and manipulate XML documents Transform XML with XSLT Use XML serialization and web services Combine XML in ADO.NET and SQL Server Create services using Windows Communication Foundation Work with LINQ Use XML with Web API and more Who This Book Is For : Those with experience in C# and .NET new to the nuances of using XML. Some XML experience is helpful.

Learn how to build an interactive source code analytics system using Roslyn and JavaScript. This concise 150 page book will help you create and use practical code analysis tools utilizing the new features of Microsoft's Roslyn compiler to understand the health of your code and identify parts of the code for refactoring. Source code is one of the biggest assets of a software company. However if not maintained well, it can become a big liability. As source code becomes larger. more complex and accessed via the cloud, maintaining code quality becomes even more challenging. The author provides straightforward tools and advice on how to manage code quality in this new environment. Roslyn exposes a set of APIs which allow developers to parse their C# and VB.NET code and drastically lower the barrier to entry for Meta programming in .NET. Roslyn has a dedicated set of APIs for creating custom refactoring for integrating with Visual Studio. This title will show readers how to use Roslyn along with industry standard JavaScript visualization APIs like HighCharts, D3.js etc to create a scalable and highly responsive source code analytics system. What You Will Learn Understand the Roslyn Syntax API Use Data Visualization techniques to assist code analysis process visually Code health monitoring matrices (from the standard of Code Query Language) Code mining techniques to identify design patterns used in source code Code forensics techniques to identify probable author of a given source code Techniques to identify duplicate/near duplicate code Who This Book is For .NET Software Developers and Architects

Distribute Actionable, Timely BI with Microsoft® SQL Server® 2016 and Power BI Drive better, faster, more informed decision making across your organization using the expert tips and best practices featured in this hands-on guide. Delivering Business Intelligence with Microsoft SQL Server 2016, Fourth Edition, shows, step-by-step, how to distribute high-performance, custom analytics to users enterprise-wide. Discover how to build BI Semantic Models, create data marts and OLAP cubes, write MDX and DAX scripts, and share insights using Microsoft client tools. The book includes coverage of self-service business intelligence with Power BI. • Understand the goals and components of successful BI • Build data marts, OLAP cubes, and Tabular models • Load and cleanse data with SQL Server Integration Services • Manipulate and analyze data using MDX and DAX scripts and queries • Work with SQL Server Analysis Services and the BI Semantic Model • Author interactive reports using SQL Server Data Tools • Create KPIs and digital dashboards • Implement time-based analytics • Embed data model content in custom applications using ADOMD.NET • Use Power BI to gather, model, and visualize data in a self-service environment

In this session, David Rose, CEO, Ditto Labs, sat with Vishal Kumar, CEO AnalyticsWeek and shared his journey as a data driven executive, best practices, shared some thought leadership in visualizations and usability. Some challenges/opportunities he's observing as an analytics-driven startup.

Timeline: 0:29 David's journey. 4:50 Bringing technology to everyday objects. 9:37 Sensor and photosensor. 13:02 Choosing the right use cases. 16:54 On deep learning. 21:49 Working on new use cases in image processing. 26:05 Ditto Labs's allure classifiers. 28:15 Challenges as an entrepreneur in an image processing company. 32:50 Technical challenges for Ditto faces. 36:58 Privacy and IoT. 40:17 Different countries, different legal norms on privacy. 42:55 Data culture and image processing company. 44:46 Opportunities in the image processing stacks.

Podcast Link: https://futureofdata.org/analyticsweek-leadership-podcast-with-david-rose-ditto-labs/

If interested in vision catalog (as discussed in the video): http://www.slideshare.net/davidloring...

David's website: enchantedobjects.com

Here's David's Bio: David is the CEO at Ditto Labs, an image-recognition software platform that scours social media photos to find brands and products.

His new book, Enchanted Objects, focuses on the future of the internet of things and how these technologies will impact how we live and work.

Prior to Ditto, David founded and was CEO at Vitality, a company that reinvented medication packaging now distributed by CVS, Walgreens, and Express Scripts.

He founded Ambient Devices, which pioneered glanceable technology: embedding internet information in everyday objects like lamps, mirrors, and umbrellas.

David holds patents for photo sharing, interactive TV, ambient information displays, and medical devices. His work has been featured at the MoMA, covered in the New York Times, WIRED, and The Economist, and parodied on the Colbert Report.

David co-teaches a popular course in tangible user interfaces at the MIT Media Lab with Hiroshi Ishii. He is a frequent speaker to corporations and design and technology conferences.

He received his BA in Physics from St. Olaf College, studied Interactive Cinema at the MIT Media Lab, and earned a Masters at Harvard.

Follow @davidrose

The podcast is sponsored by: TAO.ai(https://tao.ai), Artificial Intelligence Driven Career Coach

About #Podcast:

FutureOfData podcast is a conversation starter to bring leaders, influencers, and lead practitioners to discuss their journey to create the data-driven future.

Want to Join? If you or any you know wants to join in, Register your interest @ http://play.analyticsweek.com/guest/

Want to sponsor? Email us @ [email protected]

Keywords:

FutureOfData #DataAnalytics #Leadership #Podcast #BigData #Strategy

Today's guest is Cameron Davidson-Pilon. Cameron has a masters degree in quantitative finance from the University of Waterloo. Think of it as statistics on stock markets. For the last two years he's been the team lead of data science at Shopify. He's the founder of dataoragami.net which produces screencasts teaching methods and techniques of applied data science. He's also the author of the just released in print book Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference, which you can also get in a digital form. This episode focuses on the topic of Bayesian A/B Testing which spans just one chapter of the book. Related to today's discussion is the Data Origami post The class imbalance problem in A/B testing. Lastly, Data Skeptic will be giving away a copy of the print version of the book to one lucky listener who has a US based delivery address. To participate, you'll need to write a review of any site, book, course, or podcast of your choice on datasciguide.com. After it goes live, tweet a link to it with the hashtag #WinDSBook to be given an entry in the contest. This contest will end November 20th, 2015, at which time I'll draw a single randomized winner and contact them for delivery details via direct message on Twitter.

R in Action, Second Edition presents both the R language and the examples that make it so useful for business developers. Focusing on practical solutions, the book offers a crash course in statistics and covers elegant methods for dealing with messy and incomplete data that are difficult to analyze using traditional methods. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on time series analysis, cluster analysis, and classification methodologies, including decision trees, random forests, and support vector machines. About the Technology Business pros and researchers thrive on data, and R speaks the language of data analysis. R is a powerful programming language for statistical computing. Unlike general-purpose tools, R provides thousands of modules for solving just about any data-crunching or presentation challenge you're likely to face. R runs on all important platforms and is used by thousands of major corporations and institutions worldwide. About the Book R in Action, Second Edition teaches you how to use the R language by presenting examples relevant to scientific, technical, and business developers. Focusing on practical solutions, the book offers a crash course in statistics, including elegant methods for dealing with messy and incomplete data. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on forecasting, data mining, and dynamic report writing. What's Inside Complete R language tutorial Using R to manage, analyze, and visualize data Techniques for debugging programs and creating packages OOP in R Over 160 graphs About the Reader This book is designed for readers who need to solve practical data analysis problems using the R language and tools. Some background in mathematics and statistics is helpful, but no prior experience with R or computer programming is required. About the Author Dr. Rob Kabacoff is a seasoned researcher who specializes in data analysis. He has taught graduate courses in statistical programming and manages the Quick-R website at statmethods.net. Quotes Essential to anyone doing data analysis with R, whether in industry or academia. - Cristofer Weber, NeoGrid A go-to reference for general R and many statistics questions. - George Gaines, KYOS Systems Inc. Accessible language, realistic examples, and clear code. - Samuel D. McQuillin, University of Houston Offers a gentle learning curve to those starting out with R for the first time. - Indrajit Sen Gupta, Mu Sigma Business Solutions