Center for Data Sciences and Applied Machine Learning
CDSAML
RR Campus cdsaml@pes.edu
Research Output
0
Patents
Research Output
20
Publications
Research Funding & Royalty
₹0.0Cr/₹0.0Cr
External / PESU Funding
About CDSAML
Center for Data Science and Applied Machine Learning(CDSAML) at PES University focuses on Image Processing, Computer Vision and Pattern Recognition using technologies from Artificial Intelligence, Machine Learning and Deep learning. Social Media Analytics using technologies from Statistical Machine Learning(SML), Natural Language Processing and Information Visualization. The goal of CDSAML is to build systems and algorithms to extract knowledge, find patterns, generate insights and predictions from diverse data for various applications and visualization. The center conducts survey research, qualitative data collection, and data analysis.
Areas of Research
Our Researchers
Research Publications
Authors: Kaushik Ravi , Nypunya Devraj, Shylaja S S,
Authors: Nidhi P G, Disha M, Siddharth Soora, Pranav Bookanakere and Uma D.
Authors: Preethi P, Rohit Suresh, Mutasim M, Yashwin S, Sana Suman
Authors: Ashwini Joshi,
Tools & Technologies
OpenCV is an open source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in the commercial products
NLTK is a leading platform for building Python programs to work with human language data. It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and an active discussion forum.
Tensorflow, Theano, Keras, Caffe, Torch, Deeplearning4j, MXNet, Microsoft Cognitive Toolkit, Lasagne and BigDL.
Anaconda is the leading Open Data Science platform powered by Python for large-scale data processing, predictive analytics, and scientific computing, that aims to simplify package management and deployment.