AI News, Interpreting Confidence Intervals

Interpreting Confidence Intervals

Data science pioneer, founder, author, CEO, investor, with broad spectrum of domain expertise, technical knowledge, and proven success in bringing measurable added value to companies ranging from startups to fortune 100, across multiple industries (finance, Internet, media, IT, security) and domains (data science, operations research, machine learning, computer science, business intelligence, statistics, applied mathematics, growth hacking, IoT). Vincent

developed and deployed new techniques such as hidden decision trees (for scoring and fraud detection), automated tagging, indexing and clustering of large document repositories, black-box, scalable, simple, noise-resistant regression known as the Jackknife Regression (fit for black-box, real-time or automated data processing), model-free confidence intervals, bucketisation, combinatorial feature selection algorithms, detecting causation not correlations, and generally speaking, the invention of a set of consistent robust statistical / machine learning techniques that can be understood, implemented, interpreted, leveraged and fine-tuned by the non-expert.

About Vincent Granville

Vincent Granville a data expert who is currently based out of Seattle, Washington. Although he is based out of the pacific northwest, Vincent Granville has ...

Jon Bodner | You got your engineering in my Data Science: Addressing the reproducibility crisis

PyData DC 2016 Slides: ...

Data 8 Spring 2016 Lecture 37

Finding and interrogating historical data – Understanding Shell Shock (1/4)

For more like this subscribe to the Open University channel: Free learning from The Open ..

CHES 2017 9/27 Session VI: Security Evaluation & Session VII: FPGA Security

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