Learning from mistakes – Fixing pygpu attribute error.

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.

In the cloud – Geography agnostic enterprise using Google Cloud Platform.

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.

Pi day – Calculate 2017 digits of pi using Python3

Here is a short and elegant code to calculate 2017 digits of pi. The code is implemented in python3. In three lines of very simple python code; we are going to calculate the 2017 digits of pi. from mpmath import mp mp.dps = 2017 print(mp.pi) The output is: 3.141592653589793238462643383279502884197169399375105820974944592307816406286208998628034825342117067982148086513282306647093844609550582231725359408128481117450284102701938521105559644622948954930381964428810975665933446128475648233786783165271201909145648566923460348610454326648213393607260249141273724587006606315588174881520920962829254091715364367892590360011330530548820466521384146951941511609433057270365759591953092186117381932611793105118548074462379962749567351885752724891227938183011949129833673362440656643086021394946395224737190702179860943702770539217176293176752384674818467669405132000568127145263560827785771342757789609173637178721468440901224953430146549585371050792279689258923542019956112129021960864034418159813629774771309960518707211349999998372978049951059731732816096318595024459455346908302642522308253344685035261931188171010003137838752886587533208381420617177669147303598253490428755468731159562863882353787593751957781857780532171226806613001927876611195909216420198938095257201065485863278865936153381827968230301952035301852968995773622599413891249721775283479131515574857242454150695950829533116861727855889075098381754637464939319255060400927701671139009848824012858361603563707660104710181942955596198946767837449448255379774726847104047534646208046684259069491293313677028989152104752162056966024058038150193511253382430035587640247496473263914199272604269922796782354781636009341721641219924586315030286182974555706749838505494588586926995690927210797509302955321165344987202755960236480665499119881834797753566369807426542527862551818417574672890977772793800081647060016145249192173217214772350141441973568548161361157352552133475741849468438523323907394143334547762416862518983569485562099219222184272550254256887671790494601653466804988627232791786085784383827967976681454100953883786360950680064225125205117392984896084128488626945604241965285022210661186306744278622039194945047123713786960956364371917287467764657573962413890865832645995813390478027590099465764078951269 Happy 2017 pi day. The code… Continue reading Pi day – Calculate 2017 digits of pi using Python3

Installation notes – OpenCV in Python 3 and Ubuntu 17.04.

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.

Virtualization – Matryoshka dolls of computing.

A few weeks back I talked about various open operating systems to efficiently run some of the deep learning and simulation models. I switched back and forth between six different flavors of linux to finally settle with one. This experimentation phase is helpful in the long-run. But, for folks who want to run one particular… Continue reading Virtualization – Matryoshka dolls of computing.

Linux distros – The art of selecting one.

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.

Quantifying trust – An essential necessity for any business.

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.

What is next – The future of research.

Every year, from 2010 onward, Redmonk publishes a bi-annual comparison of the popularity of programming languages relative to one another using data from GitHub and Stack Overflow. One list is compiled for the summer and another one for the spring. Among top 15 programming languages in the spring 2016 list, only one exclusively scientific and statistical programming language is… Continue reading What is next – The future of research.

Writing better code – Parallelize

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

Innovation at its core – Making nanoscience accessible.

In this blog post, I will detail two key philosophies that are behind nanoveda. LEAP philosophy: Most important guiding philosophy of nanoveda is very simple: bringing nano-science to masses. The first product we are developing is to address one of the toughest challenges known to human-kind: controlling and curing cancer. Achieving this goal is a step-wise process. My four steps… Continue reading Innovation at its core – Making nanoscience accessible.