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April 2017 Blog Posts (92)

Build a Recurrent Neural Net in 5 min

This video was posted on Youtube by Sirajology. He explains the basics of recurrent neural networks. Then you code your own RNN in 80 lines of python (plus white-space) that predicts the sum of two binary numbers after training.

Code for this video:…


Added by Emmanuelle Rieuf on April 4, 2017 at 12:00pm — No Comments

30 Free Courses: Neural Networks, Machine Learning, Algorithms, AI

The list below is a small selection from Open Culture. We picked up classes relevant to data scientists, and removed links that no longer work at the time of writing. If you know of any other interesting courses, email me and we will include them if they are relevant.

The 78-video playlist above comes…


Added by Vincent Granville on April 4, 2017 at 11:30am — 3 Comments

Data readiness strategies of AI Start-ups

Last week, at an event on AI, I asked the panel about how investors evaluate the Data readiness of AI start-ups. This subject is close to my work and my teaching. I teach a course on Implementing Enterprise AI and also teach Data Science for IoT at the University of Oxford.  Below are my perspectives.  …


Added by ajit jaokar on April 4, 2017 at 10:00am — No Comments

DataOps – It’s a Secret

Summary:  DataOps is a series of principles and practices that promises to bring together the conflicting goals of the different data tribes in the organization, data science, BI, line of business, operations, and IT.  What has been a growing body of best practices is now becoming the basis for a new category of data access, blending, and deployment platforms that may solve data conflicts in your organization.



Added by William Vorhies on April 4, 2017 at 8:03am — 1 Comment

Top mistakes data scientists make

The rise of the data scientists continues and the social media is filled with success stories – but what about those who fail? There are no cover articles praising the fails of the many data scientists that don’t live up to the hype and don’t meet the needs of their stakeholders.

The job of the data scientist is solving problems. And some data scientists can’t solve them. They either don’t know how to, or are obsessed about the technology part of the craft and forget what the job is…


Added by Karolis Urbonas on April 3, 2017 at 11:30pm — 1 Comment

Book: Java Deep Learning Essentials

Book Description

AI and Deep Learning are transforming the way we understand software, making computers more intelligent than we could even imagine just a decade ago. Deep Learning algorithms are being used across a broad range of industries – as the fundamental driver of AI, being able to tackle Deep Learning is…


Added by Emmanuelle Rieuf on April 2, 2017 at 6:31pm — No Comments

History as a guide to IoT growth trajectory

Internet of Things (IoT) has generated a ton of excitement and furious activity. However, I sense some discomfort and even dread in the IoT ecosystem about the future – typical when a field is not growing at a hockey-stick pace . . .

“History may not repeat itself but it rhymes”, Mark Twain may have said. What history does IoT rhyme with?

 I have often used this diagram to crisply define IoT.…


Added by PG Madhavan on April 2, 2017 at 1:00pm — 1 Comment

Will Workers in Obsolete Jobs Find Refuge in Data Analysis?

Like it or not, data-driven artificial intelligence algorithms and other high-tech robotic applications are coming to fill our jobs. An analysis by PwC estimated that up to 38 percent of current American jobs could be taken over by machines within the next 15 years.

Even white-collar jobs aren’t safe, since algorithms are capable of governing sophisticated tasks for machines in ways that previously were unthinkable, such as writing or distributing pharmaceuticals. The transition has…


Added by Larry Alton on April 2, 2017 at 6:30am — 3 Comments

88 percent of all integers have a factor under 100

And 92 percent of all (positive) integers have a factor under 1,000. And how many have a factor under 6? Can you guess the answer? Read more to find out.

Clearly, the vast majority of big numbers have small factors. Also, the chance to be a prime becomes incredibly small, the bigger the number. I stumbled upon these problems when looking for new algorithms to factor a product of two large primes (more on this coming soon.) I then decided to find out what the proportion of integers…


Added by Vincent Granville on April 1, 2017 at 2:00pm — 1 Comment

Embedding Narrative Sense into Web Documents

I was joking when I entered on Google, “Where was my coworker yesterday?”  After reviewing the responses that appeared from the search engine, I continued, “What did she eat for breakfast?”  Sometimes the responses to my everyday questions seem insightful - on a certain level, interesting and intriguing.  Usually the quality of the responses is quite poor.  I assume therefore that the algorithms operating in the background don’t “understand” the sense of what I am asking.  If I were to ask,…


Added by Don Philip Faithful on April 1, 2017 at 9:30am — No Comments

Weekly Digest, April 3

Monday newsletter published by Data Science Central. Previous editions can be found here.  The contribution flagged with a + is our selection for the picture of the week.



Added by Vincent Granville on April 1, 2017 at 9:00am — No Comments

Digital Transformation in Manufacturing

Manufacturing companies have traditionally been slow to react to the advent of digital technologies like intelligent robots, drones, sensor technology,artificial intelligence, nanotechnology & 3d Printing.

Industry 4.0 has changed manufacturing. At a…


Added by Sandeep Raut on April 1, 2017 at 4:30am — No Comments

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