Saturday, December 31, 2016

Year in Review

It's been quite an interesting year to say the least.

Lots of new Machine Learning and Deep Learning tools and libraries were released into the wild reducing the barriers to entry.

I'm really hoping to turn a corner and do more writing next year. I just can't seem to be able to shake off my writer's block.

Here again is Jeff Leek's Non-comprehensive list of awesome things other people did in 2016

Sunday, July 24, 2016

Data Science Bootcamp Reviews

This post is also posted in whole / part here :

When we started this, our primary goal was to bring to light as much information as we could regarding Data Science Bootcamps. We initially published several  in-depth interviews with boootcamp founders. We’re still working on a few more and we are also embarking on the next stage.

We contacted and conducted detailed interviews with individuals who have graduated from different Data Science Bootcamps and as you might guess, we heard a lot of very interesting anecdotes.

We noticed a disparity on what we heard from the individuals we interviewed about bootcamp placements and outcomes compared to the information some bootcamps put out there.

We actually don’t think Data Science Bootcamps should guarantee placements or positive outcomes but a lot of them do imply it by using wordplay, sleight of hand or displaying statistics that are either out of date or are aggregates which may not be very useful.

A better approach in our opinion will be for the Data Science Bootcamps to publish 3 and 6 month post-mortems or detailed placement reports (at least 6 months) for each cohort they graduate.  A prospective bootcamp student would probably find it more useful to know that for a cohort, 30% of the students were not looking for a job, 15% decided this wasn’t the right path for them and of the remaining 55%, most ended up with placements or positive outcomes versus just saying the cohort had an 80% placement rate without providing any other information. So a 100% placement rate for a cohort might not always be as good as it sounds. You just only have to look behind the curtain at the details.

We know for a fact that some bootcamps kick people out that they feel will not be able to find a job and sometimes don’t include individuals that fall off the radar or aren’t able to find jobs in their placement stats.

People attend these Bootcamps for very different reasons. For some it’s probably to transition to a Data Science or Data related role, for others, it could be to skill-up and then make lateral moves within their organization or to work on their ideas and personal projects .

Over the next few weeks and months, we will be publishing some of these Data Science Bootcamp reviews here.

If you have attended and graduated from a Data Science Bootcamp and you’d like to do a review of your experience, we’d love to hear from you. Please fill this form and we’ll reach out to you to conduct the short interview.

Having this information out there helps prospective Data Science Bootcamps students understand the dynamics with each of these bootcamps and the value it will deliver for them. This will also give them enough information to decide which program is the best fit for them / their goals.

Friday, April 8, 2016

Some more interesting links-6, Tensorflow, Falcon 9 #falconhaslanded

Google outsourced TensorFlow, one of its machine learning interfaces [PDF] [Slides]
Jeff Dean on TensorFlow
Tensor Flow meetup recording

Startup Pitch Decks

Machine Intelligence Landscape 2.0

Google Self Driving Car

Open AI is really looking more like Xerox PARC and BellLabs

And the #falconhaslanded . Falcon 9 first stage landing on a Drone Ship . I guess with Elon Musk it was always really a matter of "when" and not "if".  Another step closer to re-usability and Mars