Amazon discover.bot

I recently got a new gig as Industry Analyst for Amazon’s new discover.bot business unit. I will be advising on AI chatbot technology and writing periodic articles assessing how bots are quickly evolving across a broad variety of industries. My first piece is now available as of October 30, 2019, “Should a Chatbot Reveal Itself?” I’m looking forward to following this dynamic and growing industry segment.

UCLA Extension – Intro to Data Science

I’m really excited to be teaching again! Starting April 2 and 4, 2019, I’m teaching two sections of the popular “Introduction to Data Science” course for UCLA Extension. In a previous life I taught at UNEX for 15 years, but after getting too busy as a data scientist, I had to walk away from teaching for a while. I’m happy to be returning to education now. I feel the time is right to get future data scientists up to speed to fill in the widening skills gap due to the accelerating rise in demand for data science professionals. Glad to be giving back!

[UPDATE: I am now teaching regularly for UCLA Extension, 2 classes per quarter. Due to COVID-19, all classes are virtual, but enrollment is great! My course GitHub repo is found HERE.]

Universal Standard Housing

I’m pleased to announced that I have secured a new consulting relationship with Los Angeles based Universal Standard Housing (USH), a leader and innovator in the affordable housing industry. I will be providing data science consulting services to help lead an exciting new development project. This is a great start-up company, with some very smart and dynamic people. I’m looking forward to a successful deployment of machine learning based real estate solutions.

Open Data Science

I would like to announce that I’m now working with a new up-and-comer in the industry – Open Data Science, most commonly known for their Open Data Science Conferences (ODSC) West, India, Europe, and East. More recently, the company is providing a wealth of technical resources such as articles dealing with data science tools, modeling (machine learning), AI, deep learning, data viz, data transformation, academic research, and so much more. I will be making regular contributions as a data scientist. My first contribution is “Tips for Linear Regression Diagnostics.”

[UPDATE 11/23/2020] : since my original announcement, I’ve made 80+ contributions for the ODSC blog. I just received excellent feedback from the company that my pieces were the most popular! You can read all my article HERE.

FICO Artificial Intelligence Review

I was contracted by the FICO product marketing department to review their long term use of artificial intelligence (AI) for fraud, cybersecurity and compliance (AML) solutions. All three of these areas utilize machine learning and AI for anomaly detection. The flagship of this portfolio is the Falcon Fraud Platform, and is used by ~ 10,000 financial institutions to risk score approximately 9,000 payment card transactions/sec globally. I had a blast digging into all that FICO was doing with AI, and I came up with a summary document “5 Keys to Successfully Applying Machine Learning and AI in Enterprise Fraud Detection.” Here is a list of the 5 elements I focused on for the project:

• The role of supervised and unsupervised models in fraud detection (with a focus on behavior anomaly analytics)
• The importance of large data sets in model development and training
• What are predicting features and why is domain expertise necessary in their development
• The benefits of Specialized vs. Generic models in enterprise fraud (i.e., importance of expert features)
• The role of adaptive analytics and/or self-learning AI in enterprise fraud

You can download the report here: 5_Keys_Successfully_Applying_Machine_Learning_ AI

insideBIGDATA Guide to Artificial Intelligence & Deep Learning

I’m very pleased to announce the availability of a new technology guide that I was contracted to research, develop and write – “insideBIGDATA Guide to Artificial Intelligence & Deep Learning” sponsored by NVIDIA.

This guide to artificial intelligence explains the difference between AI, machine learning and deep learning, and examines the intersection of AI and HPC. The guide includes a special section highlighting the results of a new insideBIGDATA audience survey to get readers thoughts about how they see AI, machine learning and deep learning for their own companies. The guide provides some of the survey results including numeric results, data visualization, and interpretation of the results.

You can download a copy of the guide HERE.

Machine Learning for the Fashion Industry

My long affiliation with LA’s preeminent fashion mart – The New Mart, has been a fruitful one. This collection of over 70 high-end fashion showrooms is managed by a forward-thinking team that allowed me to engage methods of statistical learning to increase the reach of their many clothing lines through use of social media data sources. I built some cool technology to yield a weekly “Fashion top 10” that serves to drive The New Mart’s social media effort. Using sentiment analysis coupled with data sources like Twitter, Facebook, Instagram and fashion blogs, spreading brand awareness is approached in a strategic and focused manner.

insideBIGDATA Guide to Scientific Research

I’m pleased to announce that I was contracted to research, develop and write a new technology guide “insideBIGDATA Guide to Scientific Research” sponsored by Dell and Intel. The goal for this Guide is to provide a road map for scientific researchers wishing to capitalize on the rapid growth of big data technology for collecting, transforming, analyzing, and visualizing large scientific data sets.

I was particularly excited about writing this guide since, in a previous life, I was a researcher in the data analysis effort for a large-scale astrophysics project.

You can download a copy of the guide HERE.

Corporate R Training at So Cal Edison

This week I started a boot camp style corporate training gig over at Southern California Edison in Irwindale. The title of the 7 week course is “Introduction to R Programming,” although I’m teaching it like an intro to data science class. The contract was arranged through UC Irvine as part of their popular data science certificate program.

The SCE group attending the class is from a broad spectrum of SCE departments including IT, business intelligence, customer analytics, power supply, and business analysis. The participants see very capable and are anxious to move into the data science realm. I’m quite pleased to take some time off my busy project work schedule for a serious teaching assignment like this. Very rewarding!

Corporate R Training at Toyota

I just completed a short Boot-Camp style corporate training gig for Toyota Financial Services. The 3 full-day session was organized by UC Irvine Extension as part of their Data Science program. I had a blast with the Toyota group consisting of Big Data and BI managers, analysts, IT personnel, and programmers. It was a very insightful group with a sincere desire to learn R, data science and machine learning. I came away quite impressed with Toyota (too bad they’re moving to Texas).