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All Blog Posts Tagged '#MachineLearning' (103)

What We Can Learn about AI and Creating Smart Products from “The Incredibles”

Nothing strikes terror into the hearts of humans more than the idea of an intelligent robot gone bad.  The fear is that a robot can acquire the ability to learn and adapt to the point of superseding their human creators…and with evil intentions.

From Gort (“The Day the Earth Stood Still”) to Sonny (“I, Robot”), films provide a wide variety of potential robot scenarios.  Only a few of these film robots have demonstrated artificial intelligence to the point…

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Added by Bill Schmarzo on January 7, 2019 at 6:03am — No Comments

Design Thinking Humanizes Data Science

The article “Cognitive Hub:  The Future of Work” and the supporting infographic (see Figure 1) provides an interesting perspective on some “technology combinations” that could transform the workplace of the future, all enabled by Artificial Intelligence (AI):

  • AI + Internet of Things (IoT) yields workplace decision support
  • AI + Human-machine Interaction…
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Added by Bill Schmarzo on January 3, 2019 at 5:14pm — No Comments

Developing a Big Data / Data Science / Design College Curriculum with Infographics

For my final class this year at the University of San Francisco School of Management, I taught the students using nothing but infographics.  Not only was it fun for me, but I think the students enjoyed being able to summarize their learnings from the semester through group discussions centered around the infographics.  The infographics provide a visual opportunity to meld the three fundamental concepts that I believe every business leader needs to understand to be…

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Added by Bill Schmarzo on December 25, 2018 at 4:30am — 2 Comments

Using the Economics Value Curve to Drive Digital Transformation

I’m missing my Thursday evening Big Data MBA classes at the University of San Francisco School of Management (though I expect my students are glad that ordeal is over).  One of my biggest learnings from this semester was around how to properly construct an actionable and measurable business hypothesis.  One of the common mistakes is starting with an overly-simplified business objective such as:

  • Improve customer subscription renewals by…
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Added by Bill Schmarzo on December 21, 2018 at 5:30am — No Comments

2019 Big Data and Data Science Predictions Through the Lens of Comedy Movies

It’s that time of year again when I look into the Crystal Skull…er, ball, and make some predictions of the continuing challenges and new trends I foresee in Big Data and Data Science for the coming year.

It’s Data “Business Model” Transformation, not Digitalization

Digital Transformation moves beyond just…

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Added by Bill Schmarzo on December 5, 2018 at 8:43am — No Comments

Updated: Difference Between Business Intelligence and Data Science

I'm reposting this blog (with updated graphics) because I still get many questions about the difference between Business Intelligence and Data Science. Hope this blog helps.

I recently had a client ask me to explain to his management team the difference between a Business Intelligence (BI) Analyst and a Data Scientist.  I frequently hear this question, and typically resort to showing Figure 1 (BI Analyst vs. Data Scientist Characteristics chart, which shows the different attitudinal…

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Added by Bill Schmarzo on December 2, 2018 at 7:00am — No Comments

Using Hypothesis Development Canvas to Predict Golden State Warrior Victories

The third annual University of San Francisco (USF) MBA class Golden State Warriors analytics exercise provided an opportunity to test the students’ ability to “Think Like a Data Scientist” with respect to identifying and quantifying variables that might be better predictors of performance for the Golden State Warriors professional basketball team. This was also an opportunity to test and fine-tune the Hypothesis Development Canvas, and boy was that an eye-opener for me. The…

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Added by Bill Schmarzo on November 28, 2018 at 1:10pm — No Comments

Dean of Big Data’s Favorite Infographic Picks of 2018

My last University of San Francisco School of Management class of the semester is coming up this week. However instead of a normally boring presentation from me to cap the semester, we are going to review a few infographics to summarize our lessons from the semester. 

I also want to use this blog to give credit to Arielle Winchester for her creativity and patience to work with me in the construction of these infographics.  Here are my Top 10 infographics from…

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Added by Bill Schmarzo on November 25, 2018 at 6:00am — No Comments

The benefits of an AI Strategy for organizations worldwide

When people hear about Artificial Intelligence, things like Deep Learning, Robots and the automation of repetitive tasks in companies often come to mind. Nowadays the Artificial Intelligence research is in niches, it's called narrow AI, not one capable of making conclusions based on common sense yet. 

The main obstacle to the mainstream…

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Added by Renato Azevedo Sant Anna on November 12, 2018 at 7:48pm — No Comments

Stop Worrying About Your Job—Human Beings are the Biggest Factor in Successful Analytics

AI and machine learning have advanced rapidly over the past few years, and many have suggested that 2019 will be the year for businesses that have waited to finally embrace this new technology. Only 15% of enterprises are currently using AI, but 31% are slated to add it to their strategy over the next 12 months, according to a Digital Trends Report by Adobe. There…

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Added by Jay Bourland on November 1, 2018 at 4:58am — No Comments

Why Is Data Science Different than Software Development?  It Starts with Data…Lots o’ DATA!!

Data science development is very different from software development, and getting the two to mesh is sometimes like trying to cobble together Tinker Toys with Lincoln Logs.  One data science expert once described the differences as:

Software development is “Measure twice; cut once,” while Data Science is “Cut, cut, cut!”

The methodologies and processes that support successful software development do not work for data science projects according to one…

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Added by Bill Schmarzo on October 17, 2018 at 4:23am — No Comments

Predict ►Prescribe ►Prevent Analytics Value Cycle

Organizations looking for justification to move beyond legacy reporting, should review this little ditty from the healthcare industry:

The Institute of Medicine (IOM) estimates that the United States loses $750 billion annually to medical fraud, inefficiencies, and other siphons in the health-care system[1].

The report identified six major areas of waste: unnecessary services ($210 billion annually); inefficient…

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Added by Bill Schmarzo on October 2, 2018 at 2:30pm — No Comments

AI and the Future of Millennials

AI has snuck into our daily lives and there is nothing to stop it. Not only does AI power autonomous vehicles, but AI already decides what products you should buy, what movies you should watch, what music you should listen to, and whom you should date. If you talk to your iPhone, Google Home, and Amazon Echo, you are talking to an AI engine that powers these personal virtual assistants. AI decides whether you are approved for a loan, determines the outcome of a job applications, identifies…

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Added by Bill Schmarzo on September 30, 2018 at 2:11pm — No Comments

Data Engineers: Nobody Puts Baby in a Corner!

Oh,the lowly data engineer.  Harvard Business Review declared the role of the data scientist as “the sexiest job in the 21stcentury.” But the data engineer labors away in near obscurity acquiring, transforming, enriching, munging and preparing data for the data scientist to do their black magic.

In addition to building data pipelines –…

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Added by Bill Schmarzo on September 26, 2018 at 6:22am — No Comments

Using Confusion Matrices to Quantify the Cost of Being Wrong

There are so many confusing and sometimes even counter-intuitive concepts in statistics.  I mean, come on…even explaining the differences between Null Hypothesis and Alternative Hypothesis can be an ordeal.  All I want to do is to understand and quantify the cost of my analytical models being wrong.

For example, let’s say that I’m a shepherd who has bad eyesight and have a hard time distinguishing between a wolf and a sheep dog.  That’s obviously…

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Added by Bill Schmarzo on September 25, 2018 at 8:42am — 1 Comment

How do you know if you’re getting value from your data?

Perhaps to no one’s surprise, the growth in companies implementing Big Data and Analytics projects continues to climb – as evidenced by the continued growth in data lakes.  As most companies begin to implement their Big Data and Analytics strategy, they struggle to show value for their efforts.  This can come from several areas:

  • According to…
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Added by Bill Schmarzo on September 22, 2018 at 7:08am — No Comments

Defining AI Not as Important as Exploiting AI

Today’s Artificial Intelligence (AI) discussions remind me of a Steve Martin skit from the early Saturday Night Live days (1979). In the skit titled “What the Hell is that?”, Steve Martin, later joined by Bill Murray, is looking in the distance at something, repeatedly asking the question “What the hell is that?”  The skit reminds me of today’s AI discussions about “What the hell is AI?”, which distracts from…

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Added by Bill Schmarzo on September 18, 2018 at 4:30am — No Comments

Understanding Type I and Type II Errors

Reviving from the dead an old but popular blog on Understanding Type I and Type II Errors

I recently got an inquiry that asked me to clarify the difference between type I and type II errors when doing statistical testing.  Let me use this blog to clarify the difference as well as discuss the potential cost ramifications of type I and type II errors. I have also provided some examples at the end of the blog[1]

In statistical test theory, the…

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Added by Bill Schmarzo on August 18, 2018 at 3:35pm — 2 Comments

Importance of Metadata in a Big Data World

Updated from original posted on April 17, 2014

The importance of metadata only continues to grow as organizations are realizing that to fully exploit the business and operational potential of machine learning, deep learning and artificial intelligence requires that the raw data be enhanced with metadata.  And while we have growing volumes of  actual data, there is even more data, or metadata, around the usage and source of the actual data.

Metadata is…

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Added by Bill Schmarzo on July 23, 2018 at 4:30am — No Comments

Digital Transformation Law #6: It’s About Monetizing the Pain

Will I ever get this digital transformation thing right? The more work I do with clients on their digital transformation initiatives, the more I realize how much I don’t know. For example, first there was the “4 Laws of Digital Transformation”:

  • Law #1: It’s About Business Models, Not Just the Business. Digital Transformation is about innovating…
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Added by Bill Schmarzo on July 11, 2018 at 9:02am — No Comments

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