I am looking forward to conducting two sessions for the upcoming Data Modeling Zone conference on Oct. 17-19 in Portland, OR. My half-day session “Data Science Primer” is Tuesday morning, Oct. 18 and my short session “Machine Learning Primer” is Wednesday morning, Oct. 19. My book publisher, Technics Publications is the host of the event and I will be doing a book signing during the show.
I’d like to announce that I will be making a webinar presentation for the upcoming “Analytics for All: The Right Start” series sponsored by All Analytics. My topic will be “Finding Data Sources, and Ensuring That It’s Good Data.” Please join me on June 9, 2016 at 2pm EDT. I’m looking forward to talking about this important topic that is on the minds of all data scientists.
I was very pleased to attend the GPU Technology Conference 2016 as the guest of host company NVIDIA on April 4-7 in Silicon Valley. I didn’t know much about NVIDIA going in, so I was eager to learn what the company brought to the table for data science and machine learning. I was delighted to find that the overarching theme of the show was “deep learning” and all the underlying technologies and applications. It was clear that NVIDIA is “all in” for deep learning and its pursuit of becoming the one generalized algorithm where domain experts aren’t needed for achieving superhuman results. I was impressed enough with the experience that I wrote a comprehensive Field Report for my readers over at insideBIGDATA to give them an in-depth perspective for what I saw.
After the GTC conference, I’m sold on deep learning coupled with GPU technology. I met a bunch of cool vendors in this space and I intend to stay in touch and utilize their products and services in future projects.
I recently was appointed to the Analytic Community Experts group for crowd sourced consultancy Wikistrat. Based in Washington DC, Wikistrat operates a global network of over 2,000 subject-matter experts working collaboratively via an online platform to help decision-makers identify solutions to complex strategic challenges. Here, I will offer my insights in data science, machine learning and big data to assist in building the wisdom that is essential for dealing with an increasingly complex world.
I’m excited to announce the availability of a new technology guide that I was contracted to research, develop and write – “insideBIGDATA Guide to Streaming Analytics” sponsored by Impetus Technologies, Inc.
Many enterprises find themselves at a key inflection point in the big data timeline with respect to streaming analytics technology. There is a huge opportunity for direct financial and market growth for enterprises by leveraging this technology. The goal of this guide is to make sense of the vendor and technology landscape. It’s important to choose a platform that will supply a proven and pre-integrated, performance-tuned stack, ease of use, enterprise-class reliability and flexibility to protect the enterprise from rapid technology changes.
You can download a copy of the guide HERE.
I was happy to be enlisted by predictive analytics giant TIBCO to be a panelist for the upcoming webcast feature “How IoT Analytics can Drive Competitive Advantage” on March 3, 2016 at 11am PT. I’ll be on the panel along with industry luminary Mike Gualtieri of Forrester Research and TIBCO’s Chief Analytics Officer Michael O’Connell. The webcast will give attendees the opportunity to learn how digital businesses are capturing greater value from big data and real-time data streams for sharper insights, real-time decision-making and competitive advantage.
To register for the webcast click HERE.
I was pleased to present last evening at the Grid110 Demo Day hosted by The New Mart, LA’s premiere fashion mart in DTLA. Grid110 is a new start-up business accelerator in partnership with the Office of the Los Angeles Mayor. My topic was putting a new face on the LA apparel industry using data science methodologies. My analysis used data sets from the Los Angeles Open Data repository. I’m a big proponent of government open data resources with the goal of improving the lives of citizens in ever more data-driven cities.
My presentation is provide below. Check out the data visualizations especially the geospatial data analysis clusters showing business starts for the past 10 years across the various industry codes that constitute the LA apparel industry. Moving forward, I will be collaborating with Grid110 in 2016 to publish a new Fashion Tech industry report, develop a new Shiny app, and collect data points for a new Fashion Tech sector database. Exciting stuff!