- Model Experiments, Tracking and Registration using MLflow on Databricks - Jan 5, 2021.
This post covers how StreamSets can help expedite operations at some of the most crucial stages of Machine Learning Lifecycle and MLOps, and demonstrates integration with Databricks and MLflow.
- Design of Experiments in Data Science - Sep 3, 2020.
Read this overview of the process of designing experiments for collecting data.
- Machine Learning Experiment Tracking - Jun 4, 2020.
Why is experiment tracking so important for doing real world machine learning?
- How To “Ultralearn” Data Science: summary, for those in a hurry - Dec 30, 2019.
For those of you in a hurry and interested in ultralearning (which should be all of you), this recap reviews the approach and summarizes its key elements -- focus, optimization, and deep understanding with experimentation -- geared toward learning Data Science.
- How To “Ultralearn” Data Science: deep understanding and experimentation, Part 4 - Dec 27, 2019.
In this fourth and final part of the ultralearning data science series, it's time to take the final steps toward developing a deep understanding of the fundamentals and learning how to experiment -- the two aspects that are the ultimate keys to ultralearning.
- Intuit: Staff Data Scientist, Experimentation Analytics [Mountain View, CA] - May 9, 2019.
Intuit is seeking a Staff Data Scientist to join our team, to help build a new business within the company in one of the hottest fintech spaces of the moment.
- Intuit: Experimentation Leader, Data Science and Analytics [Mountain View, CA] - May 9, 2019.
Seeking a Principal Experimentation Data Scientist, a creative problem solver with a passion for delivering data-driven insights, a deep knowledge of Testing and Experimentation to optimize digital experiences.
- Comet.ml – Machine Learning Experiment Management - Apr 9, 2018.
This article presents comet.ml – a platform that allows tracking machine learning experiments with an emphasis on collaboration and knowledge sharing.
- Get more insights from fewer experiments - Mar 3, 2017.
Efficient experimentation can save both time and money in the long term when it helps optimize product or process performance. This webcast shows how a dynamic model can dramatically improve outcomes.
- HP Big Data Helps Ford to Better Manage Fleets and Personalize Employee Drives - Jul 23, 2015.
HP-Ford partnership is leveraging Big Data for the next level of Telematics insights based intelligence.
- Interview: Joseph Babcock, Netflix on Discovery and Personalization from Big Data - Jun 15, 2015.
We discuss the steps involved in Discovery process at Netflix, impact due to multitude of devices, system generated logs, and surprising insights.
- Interview: Mario Vinasco, Facebook on Advancing Marketing Analytics through Rigorous Experimentation - Apr 27, 2015.
We discuss marketing analytics at Facebook, multi-channel performance assessment, success factors, lessons from Look Back feature, advice, and more.
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- Develve statistical software, free for non-commercial use - Oct 10, 2014.
Check out Develve 2.0, a six-sigma tool, the new version featuring new utilities for measure system analysis and the design of sophisticated experiments.
- Predictive Analytics Innovation Summit 2014 London: Day 2 Highlights - Jul 31, 2014.
Highlights from the presentations by Predictive Analytics leaders from Spotify, ING, Quintiles, and Riot Games on day 2 of Predictive Analytics Innovation Summit 2014 in London, UK.
- Interview: Cliff Lyon, Stubhub on Mastering the Art of Recommendation and Personalization Analytics - Jul 18, 2014.
We discuss challenges in designing recommendation and personalization systems, how to select the right metrics, and learning regarding presentation of recommendation on different channels.
- Interview: Conal Sathi, Data Scientist, Slice on Creating Value from Mining Shoppers’ e-Receipts - Jun 16, 2014.
We discuss the relevance of "Purchase Graph", Slice platform, analytical insights from mining all activity around a customer's purchase, experimentation strategy, experience of working as a data scientist and more.
- Microsoft: Sr. Software Development Engineer, Analysis and Experimentation Team - May 6, 2014.
Build a world-class experimentation service that accelerates innovations for Bing and key partners in Microsoft by testing new ideas quickly and reliably.
- Microsoft: Applied Researcher - Apr 26, 2014.
Be at the forefront of Big Data, command many thousands of machines, process petabytes of data, and not just answer the question given but define what the right question to answer is.