Workshop – The Deadly Dozen: The Top 12 Analytics Mistakes and the Techniques to Defeat Them

More statements of testimony (for the earlier version of John’s workshop)

Workshop Description

This one-day session reveals the subtle mistakes analytics practitioners often make when facing a new challenge (the “deadly dozen”), and clearly explains the advanced methods seasoned experts use to avoid those pitfalls and build accurate and reliable models.

This workshop covers:

• Antidotes: the best practices that overcome the most common flawed practices
• Intuitive explanations of resampling methods that ensure your models work on new data
• Practical tips for both the hard and the soft skills that will see your project through to implementation

In this workshop, renowned practitioner and hugely popular instructor Dr. John Elder will survey the most advanced analytics tools in the practitioner’s toolkit, with particular emphasis on resampling tools – such as cross-validation and target shuffling (a method to avert p-hacking devised by Dr. Elder) – which reveal the true accuracy of your models.

Workshop topics also include visualization, feature engineering, global optimization, criteria of merit design, ensembles, and “soft” factors that affect success, such as human cognitive biases. Attendees will also leave with an understanding of the inner workings of the most popular algorithms – including regression, decision trees, nearest neighbors, neural networks, bagging, boosting, and random forests.

Throughout the workshop day, Dr. Elder will share his (often humorous) stories from real-world applications, illuminating the technical material covered.

If you’d like to become a more expert practitioner of predictive analytics, this workshop is for you.

What you will learn:

• The 12 subtle pitfalls to watch out for on any new project
• The latest ways to increase the value of predictive models and machine learning for your business
• How to succeed when your biggest threat is not technology, but people (e.g., resistance to change)

Prerequisites:
The workshop is filled with real-world stories and explanations of methods that are visual and analogy-based, rather than mathematical. Each section is designed to make clear the gist of its concept to a complete novice, and to conclude with intriguing ideas for advanced researchers. Experience has shown that attendees who get the very most out of the course:

• Have some experience with programming, or algorithmic approaches to problem-solving
• Have taken an introductory course in probability or statistics … but most importantly
• Have a problem to solve that inspires and anchors their learning as techniques are introduced

Pricing and Registration Information

Free books:
Attendees receive a free copy of John Elder’s ebook Handbook of Statistical Analysis and 
Data Mining Applications, a PDF of all training slides from this workshop, and an official certificate of completion at the conclusion of the workshop.

Special offer: Register for both this workshop as well as Dr. Elder’s other one-day PAW workshop, “The Best of Predictive Analytics: Core Machine Learning and Data Science Techniques” (complementary but not required), and also receive his co-authored book Ensemble Methods in Data Mining: Improving Accuracy Through Combining Predictions (in Kindle form).