NATIONAL LEVEL SHORT-TERM TRAINING
PROGRAMME (NLSTTP)
on
Statistical Machine Learning (SML)
7th – 11th August, 2023
About SOA
Siksha 'O' Anusandhan (SOA) is a Deemed to
be University situated in Bhubaneswar,
Odisha. SOA was reaccredited by NAAC with
an 'A++' grade (highest grade) in 2022. It is
ranked 15th best in the University category,
27th best in the Engineering category, 16th best
in the Medical Category, 9th best in the Dental
Science, 8th best in the Law Category, 49th best
in the Research category, and 26th best in the
Overall Category by NIRF Ranking 2023,
MHRD, Govt. of India.
Programme Objective
Jointly Organized by
Centre for Data Science (CDS) and Centre for
Artificial Intelligence & Machine Learning
(CAI&ML)
Under the
Department of Computer Science and
Engineering (CSE)
Faculty of Engineering and Technology (ITER)
Siksha ‘O’ Anushandhan (Deemed to be
University), Bhubaneswar-751030,
Odisha, India
The objective of the “NATIONAL LEVEL SHORTTERM TRAINING PROGRAMME (NLSTTP) on
Statistical Machine Learning” is to provide
participants with comprehensive knowledge
and practical skills in the field of statistical
machine learning. The program aims to equip
participants with the necessary tools and
techniques to understand and apply statistical
machine learning algorithms effectively in
various domains. The specific objectives of the
program include:
1. Understanding
Statistical
Machine
Learning: Introduce participants to the
fundamental concepts, principles, and
algorithms of statistical machine learning.
Cover topics such as supervised and
unsupervised
learning,
regression,
classification, clustering, dimensionality
reduction, and model evaluation.
2. Hands-on
Experience:
Provide
participants with hands-on experience in
implementing statistical machine learning
algorithms using programming languages
such as Python or R. Encourage
participants to work on real-world
datasets and case studies to enhance
their practical skills.
3. Model Selection and Evaluation: Teach
participants how to select appropriate
models for different machine learning
tasks and evaluate their performance.
Cover techniques such as cross-validation,
hyperparameter tuning, and model
assessment metrics.
4. Feature Engineering and Preprocessing:
Familiarize participants with techniques
for feature selection, feature extraction,
and data preprocessing. Discuss methods
to handle missing data, outliers, and
categorical variables to improve model
performance.
5. Advanced Topics: Explore advanced
topics in statistical machine learning,
including ensemble methods, deep
learning, natural language processing,
and reinforcement learning. Provide
participants with insights into cuttingedge research and applications in these
areas.
6. Application in Various Domains: Illustrate
the application of statistical machine
learning techniques in diverse domains
such as finance, healthcare, marketing,
and image recognition. Help participants
understand how to adapt and customize
machine learning approaches to address
specific domain challenges.
Venue: Campus I, FE&T, ITER.
(OFFLINE MODE)
Course Contents
Day 1:
Day 2:
Day 3:
Day 4:
Day 5:
Central tendency, Dispersion,
Asymmetry, Concentration,
Distribution and Divergence.
Discrete Distribution with
examples, Continuous Distribution
with examples, LNN: Central Limit
Theorem, Bayesian Paradigm.
Essential Mathematics for
Machine Learning, Foundations of
Machine Learning, Discriminant
Function, Bayesian classifier.
Linear Regression, Logistic
Regression, Dimensionality
Reduction,
Optimization in Machine Learning.
Neural Networks (NNs),
Randomized NNs, Deep Learning
Techniques (Autoencoder, CNN).
For any query, email us at
nsttpsml2023@gmail.com
Experts
Dr. Buddhananda Banerjee
Assistant Professor,
Department of Mathematics,
Centre for Excellence in AI, IIT Kharagpur
Chief Patron
Prof. (Dr.) Manojranjan Nayak, The Founder
President, SOADU, Bhubaneswar
Patron
Prof. (Dr.) Pradipta Kumar Nanda, Vice Chancellor,
SOADU, Bhubaneswar
Finance Chair
Dr. Deepak Ranjan Nayak
Assistant Professor,
Department of Computer
Science and Engineering, MNIT Jaipur
Registration Fee: ₹ 500/(Including Accommodation)
Prof. (Dr.) Manas Kumar Mallick, Director,
SOADU, Bhubaneswar
Program Chair
Prof. (Dr.) Debahuti Mishra, SOADU, Bhubaneswar
Advisory Committee
Prof. (Dr.) P. K. Sahoo, SOADU, Bhubaneswar
Prof. (Dr.) D.N. Thatoi, SOADU, Bhubaneswar
Prof. (Dr.) Sunita Chand, SOADU, Bhubaneswar
Prof. (Dr.) Sarada P. Pati. SOADU, Bhubaneswar
Organising Chair & Co-chair
Registration
Link:
Last Date of
Registration:
Account Holder
Name:
Bank Name
Branch Name:
Account
Number:
IFSC Code:
Swift Code:
https://forms.gle/e3idBT
jywbGhLyZj8
31st July 2023
Siksha ‘O’ Anushandhan
University
Punjab National Bank
Pokhariput,
Bhubaneswar
6762002100000239
PUNB0676200
PUNBINBBBBN
Contact Details
Name
Dr. Abhijit Sutradhar
Dr. Swadhin Kumar Barisal
Mobile Number
+91 - 8598911390
+91 - 7978409113
Dr. Manoranjan Parhi, SOADU, Bhubaneswar
Dr. Alakananda Tripathy, SOADU, Bhubaneswar
Convener & Co-convener
Dr. Abhijit Sutradhar, SOADU, Bhubaneswar
Dr. Swadhin Kumar Barisal, SOADU, Bhubaneswar
Publicity Chairs
Dr. Apul Narayan Dev, SOADU, Bhubaneswar
Dr. Lambodar Jena, SOADU, Bhubaneswar
Mr. Santosh Kumar Behera, SOADU, Bhubaneswar
Technical Committee
Dr. Sayantan Guha, SOADU, Bhubaneswar
Dr. Ashis Kumar Pati, SOADU, Bhubaneswar
Dr. Amit Kumar Singh, SOADU, Bhubaneswar
Dr. Kuldeep Singh Yadav, SOADU, Bhubaneswar
Dr. Akasmika Panda, SOADU, Bhubaneswar
Dr. Sai Gopal Rayaguru, SOADU, Bhubaneswar
Dr. Kumari Manju, SOADU, Bhubaneswar
Ms. Anmol Pattanaik, SOADU, Bhubaneswar
Mr. Ayes Chinmay, SOADU, Bhubaneswar
Organizing Committee
All faculty members of CDS, CAI&ML and CSE