Showing posts from May, 2019

Fitness Apps

I have always been a fitness enthusiast. Not a fitness junky but borderline to that. Between marriage, work style pounds and that thing that affects the metabolism…how they call it.. ah, yeah. AGE! I collected pounds along the road better than plastic polluting the environment. At some point, my sleep deteriorated to the point that something had to be done and I start looking at everything to make it less bad. Weight dropped in the target of my research. I don’t take anything by the chance, when I walk into a problem, the problem must be solved. It’s not an acceptable outcome to fail only. That means multiple failures along the path to success are going to collect, the key difference is that at some point success must be reached. So after working hard at it, I lost 21 pounds of pure lard that were making my sleep and my wardrobe setup a facebook status: complicated. My diet is governed by an AI that I actively work on called FLINT. The journey of that project is documented 

When you don’t use your own product…

When building any product, you should do one thing above anything else.  Use it  and use it regularly  like your life and lifestyle depend on it. You will find plenty of real issues than otherwise. Who builds, design and manages  hotels  clearly sleep at home and never actually depends on the product. I am confident they use it on occasion. Just like any QA would check quality and specs matching of an about to be released product.  There’s a key difference when it comes to accommodations, like hotels, and that requires not crossing a checklist but design for human experience. Today, all that QA work is done by consumption principle which leads to cost savings and operational efficiency rather than life measurable quality. I am not the only one thinking in those terms . In addition to what has been mentioned by One Mile At A Time  blog , I want to share my views on what the accommodation business is getting 100% wrong and particularly in the US. My travel habits/cus

Deep Learning on Mac

If you have an iMac it’s super-extra likely that you have an AMD graphic card which makes your data science hobby/life harder than it should be when trying to train Deep Learning models. There are three possible way out: Buy an  eGPU  Box and an NVidia card, this road is going to be very bumpy with occasional tornados. Like compiling every new release of Tensorflow in GPU mode. Boot on Linux, with an external drive, then using AMD  ROCm Using Keras with  PlaidML , an  OpenCL  compatible backend As the third solution is by far the simplest and less intrusive option I am relying on this option as much as possible for most of my daily hobby/work.  For the cases that cannot be handled by this solution and for long training, I continue using Google Cloud as my main TPU/GPU Cloud. On occasions, I don’t want to deal with all the mess of a platform that is regularly neglected by Apple when it comes to data science and in those cases, I fire up my corner dust collecting machine th

Install TensorFlow v1.x and Keras on macOS

Image macOS Mojave: Install TensorFlow and Keras for Deep Learning - PyImageSearch Inside this guide you will learn how to configure your macOS Mojave system for deep learning with TensorFlow and Keras. BY far the best guide on the net on how to install TensorFlow on macOS. Absolutely well done. The book and other training material are also of the highest quality I have seen out there.