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Erik Gfesser

📍 Greater Chicago Area

Implementing Databricks for Data Science and Engineering Teams: Part 1

A case study I wrote about a recent client project implementing Azure Databricks for data science and engineering teams was recently published (April 9, 2019). This write-up is the first of a two part series covering the first half of a client engagement with my team. (The original post can

Manuscript Review: "Project Decisions"

An editor for a publisher reached out to me via LinkedIn on January 8, 2019 with an opportunity to provide input on the second edition of a book in exchange for a flat fee. I was given 1 calendar month to complete the review, and I submitted my feedback on

Personal Reading List: 2Q2019

My personal reading list for April, May, and June 2019. Color Key: Special Notes, Completed Reading. Updated throughout the Quarter. At Bat (Schnell) The Model Thinker: What You Need to Know to Make Data Work for You, by Scott E. Page, Basic Books, 2018. Thinking Architecturally: Lead Technical Change Within

New Book Review: "Applied Predictive Analytics"

New book review for Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst, by Dean Abbott, Wiley, 2014, reposted here: Copy provided by Amazon. Abbott is sure to discuss his philosophy and approach at the outset. "This book describes the predictive modeling process from the perspective of

Media Query Source: Part 17 - ITPro Today (US digital magazine); Are programming languages key to the evolution of machine learning?

* ITPro Today (US digital magazine) * Reaction to Facebook Chief AI Scientist * Python's popularity is relatively recent * "Best" programming languages often don't win My responses ended up being included in an article at ITPro Today (June 27, 2019). Extent of verbatim quote highlighted in orange,

New Book Review: "An Introduction to Machine Learning Interpretability"

New book review for An Introduction to Machine Learning Interpretability, by Patrick Hall and Navdeep Gill, O'Reilly, 2018, reposted here: Copy provided by Dataiku. The content of this freely made book provides an introduction to the perceived need for machine learning interpretability, and how satisfaction might be fulfilled

Jumpstarting an AWS Database Product Selection Effort (Published January 10, 2019)

A case study I wrote about a recent client project jumpstarting an AWS database product selection effort was recently published (January 10, 2019). While all database service offerings were considered, we ended up focusing on Amazon DynamoDB and Amazon Aurora using additional AWS services along the way to prove out

Personal Reading List: 1Q2019

My personal reading list for January, February, and March 2019. Color Key: Special Notes, Completed Reading. Updated throughout the Quarter. At Bat (Schnell) An Introduction to Machine Learning Interpretability, by Patrick Hall and Navdeep Gill, O'Reilly, 2018. Copy provided by Dataiku. AWS Certified Solutions Architect Associate All-in-One Exam

New Book Review: "High Performance Spark"

New book review for High Performance Spark: Best Practices for Scaling and Optimizing Apache Spark, by Holden Karau and Rachel Warren, O'Reilly, 2017, reposted here: The authors state in their preface that "this book is intended for those who have some working knowledge of Spark, and may

New Book Review: "Spark: The Definitive Guide"

New book review for Spark: The Definitive Guide, by Bill Chambers and Matel Zaharla, O'Reilly 2018, reposted here: Copy provided by O'Reilly. Over the past few months, I've had the chance to work through three related books in the following order: "Spark: The