We talked about:

Ben’s background AI evangelism Ben’s first experiences speaking in public Becoming a great speaker  Key Takeaways and Call to Action Making a good introduction Being Remembered Writing a talk proposal for conferences Landing a keynote Good topics to start talks on Pitching a solution talk to meetup organizers Top public speaking skill to acquire Book recommendations

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

We discussed monetization roles and the capabilities people need to move into those roles.

The key roles are ML Researcher, ML Architect, and ML Product Manager.

We talked about:

Vin's career journey

What does it mean to "monetize machine learning" Important monetization metrics Who should we have on the team to make a project successful Machine Learning Researcher (applied and scientist) - background, responsibilities, and needed skills Developing new categories  The best recipe for a startup: angry users + data scientists What research actually is ML Product Manager - background, responsibilities, and needed skills How product managers can actually manage all their responsibilities (and they have a lot of them!) ML Architect - background, responsibilities, and needed skills Path to becoming an architect  How should we change education to make it more effective  Important product metrics

And more! 

Links:

https://twitter.com/v_vashishta​ https://linkedin.com/in/vineetvashishta​ https://databyvsquared.com/​

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

We talked about: 

Admond's career journey What is personal brand How Admond started being active online Publishing on medium and LinkedIn Idea generation process and tools Other platforms Podcasts Offline presence 1x1 meetings Speaking on conferences Having confidence to publish Selling online courses Personal values Admond's course

And many other things

Links:

https://twitter.com/admond1994 https://linkedin.com/in/admond1994 https://buzzsumo.com https://feedly.com/ https://lunchclub.com/ https://thelead.io/data-scientist-personal-brand-toolkit?utm_medium=instructor&utm_source=admond

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

Did you know that there are 3 types different types of data scientists? A for analyst, B for builder, and C for consultant - we discuss the key differences between each one and some learning strategies you can use to become A, B, or C.

We talked about:

Inspirations for memes  Danny's background and career journey The ABCs of data science - the story behind the idea Data scientist type A - Analyst  Skills, responsibilities, and background for type A Transitioning from data analytics to type A data scientist (that's the path Danny took) How can we become more curious? Data scientist B - Builder  Responsibilities and background for type B Transitioning from type A to type B Most important skills for type B Why you have to learn more about cloud  Data scientist type C - consultant Skills, responsibilities, and background for type C Growing into the C type Ideal data science team Important business metrics Getting a job - easier as type A or type B? Looking for a job without experience Two approaches for job search: "apply everywhere" and "apply nowhere" Are bootcamps useful? Learning path to becoming a data scientist Danny's data apprenticeship program and "Serious SQL" course  Why SQL is the most important skill R vs Python Importance of Masters and PhD

Links:

Danny's profile on LinkedIn: https://linkedin.com/in/datawithdanny Danny's course: https://datawithdanny.com/ Trailer: https://www.linkedin.com/posts/datawithdanny_datascientist-data-activity-6767988552811847680-GzUK/ Technical debt paper: https://proceedings.neurips.cc/paper/2015/hash/86df7dcfd896fcaf2674f757a2463eba-Abstract.html

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

We talked about:

How we make decisions with machine learning What is decision optimization  Specifying the decision function Emulation for making the best decisions Decision optimization and reinforcement learning Getting started with decision optimization Trends in the industry

Links:

https://datatalks.club/people/danbecker.html https://www.decision.ai/​

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

We covered:

What is a feature store Problems it solves When to use a feature store  When not to use a feature store The main components When a team should start using a feature store 

Links:

Feast: https://feast.dev/ https://www.tecton.ai/blog/what-is-a-feature-store/  https://docs.greatexpectations.io/en/latest/reference/core_concepts.html

Join DataTalks.Club: https://datatalks.club​​​

In this episode, Dory and Anna talk about some new data and publications; we interview ICPSR's Shane Redman about what French and German data, a beach mural, and falafel have in common.; and laughter erupts when Dory introduces herself as Anna

Links from this episode;

Estimating the Financial Costs of Victimization, United States, 2017-2018 (ICPSR 37260: https://www.icpsr.umich.edu/web/ICPSR/studies/37260

Survey of Household Economics and Decisionmaking (SHED) 2020: Supplemental Survey, United States (ICPSR 37921: https://doi.org/10.3886/ICPSR37921

Research on Offender Decision-Making and Desistance From Crime: A Multi-Theory Assessment of Offender Cognition Change, United States, 2015-2019 (ICPSR 37457: https://doi.org/10.3886/ICPSR37457

Data-related Publication: Does information change attitudes toward immigrants? Links to this publication and associated data are available through our Bibliography of Data-Related Publications: https://www.icpsr.umich.edu/web/ICPSR/search/publications?start=0&ARCHIVE=ICPSR&PUBLISH_STATUS=PUBLISHED&sort=score%20desc%2CTITLE_SORT%20asc&rows=50&q=%22Does%20Information%20Change%20Attitudes%20Toward%20Immigrants%22

Learn more about ICPSR's Physical Data Enclave: https://www.icpsr.umich.edu/web/about/cms/2507

Learn. more about the French and German data available at ICPSR through this introductory webinar: "French and German Data at ICPSR: New Opportunities for Comparative Cross-Country Research": https://www.youtube.com/watch?v=SizDiWB_608

Summer Program scholarships: https://www.icpsr.umich.edu/web/pages/sumprog/scholarships/index.html

See all of ICPSR's upcoming events: https://www.icpsr.umich.edu/web/pages/about/events.html

We talked about 

open source getting started with open source convincing your employer to contribute to open source public speaking the checklist for open source projects the role of research advocate

And many more things!

Links from Vincent:

https://www.youtube.com/watch?v=68ABAU_V8qI&t=975s&ab_channel=PyData https://www.youtube.com/watch?v=kYMfE9u-lMo&t=958s&ab_channel=PyData https://koaning.io/projects.html https://calmcode.io/ https://makenames.io/ https://koaning.github.io/clumper/api/clumper.html

Join DataTalks.Club: https://datatalks.club​

We talked about:

The role of mentoring in career Looking for mentors and preparing for mentoring sessions as a mentee Becoming a mentor

And many other things! 

Links:

Rahul's profile on the mentoring club: https://www.mentoring-club.com/the-mentors/rahul-jain Rahul's article about mentoring: https://rahulj51.github.io/career/coaching/mentoring/2020/06/22/career-coaching.html

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

Get started with an accelerated introduction to the R ecosystem, programming language, and tools including R script and RStudio. Utilizing many examples and projects, this book teaches you how to get data into R and how to work with that data using R. Once grounded in the fundamentals, the rest of Practical R 4 dives into specific projects and examples starting with running and analyzing a survey using R and LimeSurvey. Next, you'll carry out advanced statistical analysis using R and MouselabWeb. Then, you’ll see how R can work for you without statistics, including how R can be used to automate data formatting, manipulation, reporting, and custom functions. The final part of this book discusses using R on a server; you’ll build a script with R that can run an RStudio Server and monitor a report source for changes to alert the user when something has changed. This project includes both regular email alerting and push notification. And, finally, you’ll use R to create a customized daily rundown report of a person's most important information such as a weather report, daily calendar, to-do's and more. This demonstrates how to automate such a process so that every morning, the user navigates to the same web page and gets the updated report. What You Will Learn Set up and run an R script, including installation on a new machine and downloading and configuring R Turn any machine into a powerful data analytics platform accessible from anywhere with RStudio Server Write basic R scripts and modify existing scripts to suit your own needs Create basic HTML reports in R, inserting information as needed Build a basic R package and distribute it Who This Book Is For Some prior exposure to statistics, programming, and maybe SAS is recommended but not required.

Customize the SAS Stored Process web application to create amazing tools for end users. This book shows you how to use stored processes—SAS programs stored on a server and executed as required by requesting applications. Never before have there been so many ways to turn data into information and build applications with SAS. This book teaches you how to use the web technologies that you frequently see used on impressive websites. By using SAS Stored Processes, you will be able to build applications that exploit CSS, JavaScript, and HTML libraries and enable you to build powerful and impressive web applications using SAS as the backend.While this approach is not common with SAS users, some have had amazing results. People who have SAS skills usually do not have web development skills, and those with web development skills usually do not have SAS skills. Some people have both skills but are unaware of how to connect them with the SAS Stored Process web application. This book shows you how to leverage your skills for success. What You Will Learn Know the benefits of stored processes Write your own tools in SAS Make a stored process generate its own HTML menu Pass data between stored processes Use stored processes to generate pure JavaScript Utilize data generated by SAS Convert a SAS program into a stored process Who This Book Is For SAS programmers looking to improve their existing programming skills to develop web applications, and programming managers who want to make better use of the SAS software they already license

Learn to create stunning animated and interactive charts using Highcharts and Angular. Use and build on your existing knowledge of HTML, CSS, and JavaScript to develop impressive dashboards that will work in all modern browsers. You will learn how to use Highcharts, call backend services for data, and easily construct real-time data dashboards. You'll also learn how you can club your code with jQuery and Angular. This book provides the best solutions for real-time challenges and covers a wide range of charts including line, area, maps, plot, different types of pie chart, Gauge, heat map, Histogram, stacked bar, scatter plot and 3d charts. After reading this book, you'll be able to export your charts in different formats for project-based learning. Highcharts is one the most useful products worldwide for develop charting on the web, and Angular is well known for speed. Using Highcharts with Angular, developers can build fast, interactive dashboards. Get up to speed using this book today. What You’ll Learn How to develop interactive, animated dashboards How you can implement Highcharts using Angular How to develop a real-time application with the use of WebAPI, Angular, and Highcharts How to create interactive styling themes and colors for a dashboard Who This Book Is For This book is aimed at developers, dev leads, software architects, students or enthusiasts who are already familiar with HTML, CSS, and JavaScript.

Did fake Twitter accounts help sway a presidential election? What can Facebook and Reddit archives tell us about human behavior? In Mining Social Media, senior BuzzFeed reporter Lam Thuy Vo shows you how to use Python and key data analysis tools to find the stories buried in social media. Whether you’re a professional journalist, an academic researcher, or a citizen investigator, you’ll learn how to use technical tools to collect and analyze data from social media sources to build compelling, data-driven stories. Learn how to: •Write Python scripts and use APIs to gather data from the social web •Download data archives and dig through them for insights •Inspect HTML downloaded from websites for useful content •Format, aggregate, sort, and filter your collected data using Google Sheets •Create data visualizations to illustrate your discoveries •Perform advanced data analysis using Python, Jupyter Notebooks, and the pandas library •Apply what you’ve learned to research topics on your own Social media is filled with thousands of hidden stories just waiting to be told. Learn to use the data-sleuthing tools that professionals use to write your own data-driven stories.

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.

Dive into the world of data visualization with 'Learn D3.js'. This comprehensive guide introduces D3.js-the leading JavaScript library for creating interactive, data-driven visualizations on the web. By following practical examples, you'll understand core concepts of D3.js, learn to implement various types of visualizations, and develop skills to bring dynamic, responsive graphics to your projects. What this Book will help me do Master the fundamentals of D3.js and use it to produce stunning web-based data visualizations. Bind data to the DOM using D3.js and configure interactive transitions and animations. Gain experience generating a multitude of chart types such as bar, pie, scatter charts, and more. Incorporate user interactivity into your visualizations using D3.js effectively. Work with map-based data visualizations using GIS data and various geographical projections. Author(s) Helder da Rocha is an experienced developer and educator with a passion for data visualization. With a solid background in JavaScript and web technologies, he has crafted this book to make the complexities of D3.js accessible and engaging. His approach emphasizes practical, hands-on learning, nurturing both new and seasoned developers alike. Who is it for? Are you a web developer, designer, or data scientist aiming to create interactive data visualizations for the web? If you have foundational knowledge of HTML, CSS, and JavaScript, this book is your perfect guide. Whether you're dipping your toes into web-based charts or seeking to craft advanced interactive graphics, 'Learn D3.js' is tailored to empower your journey.

This IBM® Redbooks® publication covers IBM TS7700 R4.2. The IBM TS7700 is part of a family of IBM Enterprise tape products. This book is intended for system architects and storage administrators who want to integrate their storage systems for optimal operation. Building on over 20 years of virtual tape experience, the TS7760 now supports the ability to store virtual tape volumes in an object store. The TS7700 has supported off loading to physical tape for over two decades. Off loading to physical tape behind a TS7700 is utilized by hundreds of organizations around the world. Using the same hierarchical storage techniques, the TS7700 can also off load to object storage. Given object storage is cloud based and accessible from different regions, the TS7760 Cloud Storage Tier support essentially allows the cloud to be an extension of the grid. As of the release of this document, the TS7760C supports the ability to off load to IBM Cloud Object Storage as well as Amazon S3. To learn about the TS7760 cloud storage tier function, planning, implementation, best practices, and support see IBM Redpaper IBM TS7760 R4.2 Cloud Storage Tier Guide, redp-5514 at: http://www.redbooks.ibm.com/abstracts/redp5514.html The IBM TS7700 offers a modular, scalable, and high-performance architecture for mainframe tape virtualization for the IBM Z® environment. It is a fully integrated, tiered storage hierarchy of disk and tape. This storage hierarchy is managed by robust storage management microcode with extensive self-management capability. It includes the following advanced functions: Improved reliability and resiliency Reduction in the time that is needed for the backup and restore process Reduction of services downtime that is caused by physical tape drive and library outages Reduction in cost, time, and complexity by moving primary workloads to virtual tape More efficient procedures for managing daily backup and restore processing Infrastructure simplification through reduction of the number of physical tape libraries, drives, and media TS7700 delivers the following new capabilities: TS7760C supports the ability to off load to IBM Cloud Object Storage as well as Amazon S3 8-way Grid Cloud consisting of any generation of TS7700 Synchronous and asynchronous replication Tight integration with IBM Z and DFSMS policy management Optional Transparent Cloud Tiering Optional integration with physical tape Cumulative 16Gb FICON throughput up to 4.8GB/s 8 IBM Z hosts view up to 496 8 equivalent devices Grid access to all data independent of where it exists The TS7760T writes data by policy to physical tape through attachment to high-capacity, high-performance IBM TS1150 and IBM TS1140 tape drives installed in an IBM TS4500 or TS3500 tape library. The TS7760 models are based on high-performance and redundant IBM POWER8® technology. They provide improved performance for most IBM Z tape workloads when compared to the previous generations of IBM TS7700.

This book, 'Learn Chart.js', serves as a comprehensive guide to mastering Chart.js for creating stunning web-based data visualizations. By combining JavaScript, HTML5 Canvas, and Chart.js, you will understand how to turn raw data into interactive visual stories. What this Book will help me do Develop skills to create interactive and engaging data visualizations using the Chart.js library. Learn to efficiently load, parse, and handle data from external formats like CSV and JSON. Understand different chart types offered by Chart.js and learn when to best use each one. Gain the ability to customize Chart.js charts, such as adjusting properties for styling or animations. Acquire hands-on experience with practical examples, equipping you to apply what you learn in real-world scenarios. Author(s) Helder da Rocha brings his extensive experience in programming and software development to this book, offering readers a clear and practical approach to mastering Chart.js. With a deep understanding of data visualization and web technologies, he conveys complex concepts in a straightforward way. Who is it for? This book is ideal for web developers, data analysts, and designers who have basic proficiency in HTML, CSS, and JavaScript. It is particularly suited for professionals looking to create impactful web-based data visualizations using open-source tools. Additionally, the book assumes no prior knowledge of the Canvas element, making it accessible for Chart.js beginners.

"Hands-On Dashboard Development with Shiny" provides a focused and practical guide for developing polished and professional dashboards using R and the Shiny framework. Through applied examples, you'll explore techniques in HTML, CSS, and Bootstrap to elevate your Shiny apps' interface and functionality. The book ensures a comprehensive learning experience by focusing on creating custom interfaces and layouts. What this Book will help me do Create Shiny interfaces using pure HTML to achieve full customization Enhance your R Shiny dashboards with powerful layout functions for professional designs Utilize Bootstrap themes in Shiny for consistent and aesthetically pleasing interfaces Generate interactive dashboards complete with icons and notification elements Develop and distribute R Markdown reports directly from Shiny applications Author(s) Chris Beeley is an experienced data scientist and a frequent R Shiny practitioner. With years of experience building Shiny applications and working on data visualization in professional settings, Chris brings practical and precise teaching to this book. He is passionate about making knowledge accessible and guiding learners through hands-on and engaging content. Who is it for? This book is ideally suited for developers and data analysts who have prior experience with Shiny and wish to delve deeper into customizing their applications' design. If you want to extend your Shiny apps using HTML, CSS, and layouts via Bootstrap, this book is perfect for you. It equips you with the skills to build advanced dashboards efficiently. Whether you're looking to create more visually appealing apps or enhance your UI skills, this resource caters to your needs.

Build interactive, data-driven websites with the potent combination of open source technologies and web standards, even if you have only basic HTML knowledge. In this update to this popular hands-on guide, you’ll tackle dynamic web programming with the latest versions of today’s core technologies: PHP, MySQL, JavaScript, CSS, HTML5, and key jQuery libraries. Web designers will learn how to use these technologies together and pick up valuable web programming practices along the way—including how to optimize websites for mobile devices. At the end of the book, you’ll put everything together to build a fully functional social networking site suitable for both desktop and mobile browsers. Explore MySQL, from database structure to complex queries Use the MySQLi extension, PHP’s improved MySQL interface Create dynamic PHP web pages that tailor themselves to the user Manage cookies and sessions and maintain a high level of security Enhance the JavaScript language with jQuery and jQuery mobile libraries Use Ajax calls for background browser-server communication Style your web pages by acquiring CSS2 and CSS3 skills Implement HTML5 features, including geolocation, audio, video, and the canvas element Reformat your websites into mobile web apps

This book provides a complete and modern guide to web scraping, using Python as the programming language, without glossing over important details or best practices. Written with a data science audience in mind, the book explores both scraping and the larger context of web technologies in which it operates, to ensure full understanding. The authors recommend web scraping as a powerful tool for any data scientist’s arsenal, as many data science projects start by obtaining an appropriate data set. Starting with a brief overview on scraping and real-life use cases, the authors explore the core concepts of HTTP, HTML, and CSS to provide a solid foundation. Along with a quick Python primer, they cover Selenium for JavaScript-heavy sites, and web crawling in detail. The book finishes with a recap of best practices and a collection of examples that bring together everything you've learned and illustrate various data science use cases. What You'll Learn Leverage well-established best practices and commonly-used Python packages Handle today's web, including JavaScript, cookies, and common web scraping mitigation techniques Understand the managerial and legal concerns regarding web scraping Who This Book is For A data science oriented audience that is probably already familiar with Python or another programming language or analytical toolkit (R, SAS, SPSS, etc). Students or instructors in university courses may also benefit. Readers unfamiliar with Python will appreciate a quick Python primer in chapter 1 to catch up with the basics and provide pointers to other guides as well.