Date : 18-07-2019 & 19-07-2019
Time : 09:45 AM – 03:10 PM
Day 1: Resource Person
Dr. S Kannimuthu
Department of Information Technology
Karpagam College of Engineering, Coimbatore
Day 2: Resource Person
Mr. A. Bharanidharan
Assistant Professor (Sl.Gr)
Department of Computer Science and Engineering
Sri Ramakrishna Engineering College, Coimbatore
The Department of Computer Science and Engineering organized a Two Days National Level Workshop on “Predictive Data Analytics Using Python and R Programming”on 18.07.2019 & 19.07.2019 at CC1 Laboratory.
The workshop was designed for researchers intended in analytics at any stage of their careers, including undergraduate and graduate students, faculties and research scholars. The workshop emphasized hands-on sessions on Predictive modeling, Machine Learning Algorithms using Python and R. Students, Research Scholar and faculty members from various colleges attended the workshop.
Day 1: Dr. S Kannimuthu, Associate Professor, Department of Information Technology, Karpagam College of Engineering, Coimbatore was the resource person for the session. The students were taught to code in Predictive Data Analytics like Neural Networks, Linear Regression, Bayesian Classification, Decision Tree, k-NN, Clustering, Dimensionality Reduction (PCA & LDA) using python packages such as NumPy, SciPy by the guest speaker. The speaker also addressed on Research Issues and Applications of Predictive Analytics.
Day 2: Mr. A. Bharanidharan, Assistant Professor (Sl.Gr), Department of Computer Science and Engineering, Sri Ramakrishna Engineering College sharing his views on Clustering & Classification such as K nearest neighbor, Naive Bayes Classifier, Support Vector Machine.Participants were briefed about,
- Neural Networks
- Linear Regression
- Bayesian Classification
- Decision Tree
- k-NN, Clustering
- Dimensionality Reduction (PCA & LDA) using python packages such as NumPy, SciPy
60 external participants (Students/Faculty/Research Scholars) had an effective knowledge sharing session over the two day period . The feedback received was very commendable in all aspects.