Pre-Enrollment

21st February 2027

Final Paper Submission

26th February 2027

Registration Deadline

8th March`2027

Conference Date

23rd Mar - 24th Mar 2027

Call for Papers

The International Conference on Machine Learning Techniques for Big Data Applications invites researchers, academicians, industry experts, and practitioners to submit original and high-quality research contributions. This conference serves as a global platform for presenting innovative ideas, exchanging knowledge, and fostering interdisciplinary collaboration.

Focusing on key research areas such as Big Data, Machine Learning, Information Technology, the conference aims to bridge theoretical advancements with real-world applications.

Authors are invited to submit papers addressing, but not limited to, the following areas:

01
Supervised Learning For Big Data
02
Unsupervised Learning Techniques
03
Deep Learning Applications In Big Data
04
Feature Selection Methods For Big Data
05
Scalable Machine Learning Algorithms
06
Big Data Preprocessing Techniques
07
Real-time Machine Learning Applications
08
Machine Learning For Fraud Detection
09
Data Mining Techniques For Big Data
10
Big Data In Social Media Analysis
11
Machine Learning For Customer Insights
12
Transfer Learning In Big Data Contexts
13
Ensemble Methods For Big Data
14
Big Data Analytics For Marketing
15
Reinforcement Learning Applications
16
Machine Learning In Telecommunications
17
Challenges In Big Data Analytics
18
Big Data Analytics For Risk Assessment
19
Machine Learning For Energy Management
20
Applications Of Ai In Big Data
Conference Registration

To confirm your participation and secure your presentation slot, authors of accepted papers must complete the registration. Early registration is highly recommended to enjoy discounted fees.

Register Now to Confirm Participation
Publication & Submission

Present your findings to a global audience. All accepted papers are eligible for publication in ISER-affiliated journals and conference proceedings, providing you with maximum academic visibility.

Submit Your Paper for Review