Taksha Center for Data Science (TCDS)

Introduction

At the Taksha Center of Data Science (TCDS), we’re excited about Data Science! Wherever you are and whatever you are doing you will be using data, all the time, in one way or another. Data and data science have become ubiquitous. Data science is continuously improving and simplifying the way in which we use data. At Taksha we have access to data spanning nearly every field of endeavor, as well as the tools and processes of data science to make sense of that data. 

At TCDS, we are engaged in:

Analytics: We make available descriptive, predictive and prescriptive analytical methods.  We routinely use supervised, unsupervised and blended methods to learn from data providing answers to complex real-world challenges in business, healthcare and the sciences. 

Machine Learning: We use machine learning to develop and train a model on a data set to make predictions that inform decision-making. This includes information on how to optimize systems. Our machine learning algorithms include classification and regression algorithms that utilize linear, logistic and Bayesian methods. Taksha’s machine learning also implements convolutional and recurrent networks and regression in TensorFlow TM. We make use of jupyter notebooks to source and share code for TensorFlow TM.  

Functional Programming Methods: We support all data science endeavors and include: Python with NumPy, SciPy and Pandas; JavaScript as well as other scripting methods; R; and, Matlab/Octave. We routinely use additional programming languages including Java with NetBeans, C, C++, and Fortran.

TCDS Chair:

Marvine Hamner, DSc

TCDS Technical Advisory Council (TAC):

TBA

TCDS Events

TBA