I am part of a great AI community in New York. Today was the fourth week of an ongoing effort to share the practical tricks to developing a natural language processing pipe line using deep learning. This effort was borne out of my efforts to engage the community to develop a greater understanding of how… Continue reading Learning from mistakes – Fixing pygpu attribute error.
We recently developed an incredible machine learning workstation. It was born out of necessity, when we were developing image recognition algorithms for cancer detection. The idea was so incredibly powerful, that we decided to market it as a product to help developers in implementing artificial intelligence tools. During this launch process, I came across an interesting article… Continue reading Hardware for artificial intelligence – My wishlist.
In a previous post I discussed how easy it was to setup machine learning libraries in python using virtual machines (vm) hosted in the cloud. Today, I am going to add more details to it. This post covers how to make machine learning code run faster. This post will help any user compile a tensorflow… Continue reading Fine tuning the cloud – Making machines learn faster.
The concept of geography/location agnostic enterprise is very simple. Whether I am in Beijing or Boston, Kent or Kentucky, New Delhi or New York, Silicon Valley or Silicon Wadi, Qatar or Quebec; I should have access to a standard set of tools to run the company. Moving around geographic locations are hard challenge for any enterprise.… Continue reading In the cloud – Geography agnostic enterprise using Google Cloud Platform.
These are my installation notes for OpenCV in Ubuntu 17.04 linux for python3. These notes will help start a computer vision project from scratch. OpenCV is one of the most widely used libraries for image recognition tasks. The first step is to fire-up the linux terminal and type in the following lines of commands. These first… Continue reading Installation notes – OpenCV in Python 3 and Ubuntu 17.04.
I have decided to migrate all of the programming environments to linux . The reason is simplicity of linux to run Python and R. I am often befuddled by common dependency issues, which linux seems to have avoided. This is especially true for Python. An added advantage is the ability to run very sophisticated deep learning… Continue reading Linux distros – The art of selecting one.
This post is an evolving set of ideas to quantify trust in decision making systems and processes. For me, an empirical definition of trust is the relative distance of a decision from the ground truth. Quantifying and optimizing trust in decision making systems are therefore highly important. This process will make systems that are involved… Continue reading Quantifying trust – An essential necessity for any business.
Today, I am going to share a secret recipe for writing beautiful and efficient code that I learned, while creating simulation models for nanoveda. Nanoveda is using advanced nanoscale simulations to design next generation cancer therapeutics. The secret recipe is: parallelizing code. Most modern PCs have a multicore processor inside it. We seldom code to exploit all… Continue reading Writing better code – Parallelize
For 2017, my new year resolution is to organize and share my thoughts on my website. I have added this blog, to share my ideas and my life being a doctor, neuroscientist, researcher in applied artificial intelligence and my hobbies in PC gaming & green living. Join me in this journey.