The Machine Learning Lab is a state-of-the-art facility designed to provide hands-on
experience and foster innovation in the field of machine learning (ML). It serves as a hub for
students, researchers, and educators to explore, experiment, and develop intelligent systems
and algorithms that learn from data. This lab equips learners with practical skills to tackle
real-world challenges in various domains such as healthcare, finance, transportation, and
artificial intelligence.
 Machine Learning for Data Science
 Generative AI
 Deep Learning
 Natural Language Processing
 Computer Vision and its applications
Key Features
1. High-Performance Infrastructure:
o Advanced computing systems equipped with GPUs for training and testing
complex ML models.
o Preloaded datasets from repositories like Kaggle, UCI Machine Learning
Repository, and public APIs for practice and research.
o
2. Cutting-Edge Tools and Frameworks:
o Access to popular ML libraries and frameworks such as TensorFlow, PyTorch,
and Scikit-learn.
o Availability of software for data preprocessing, model building, and
evaluation, including Jupyter Notebook and Anaconda.

3. Experimentation and Prototyping:
o Opportunities to prototype solutions in natural language processing (NLP),
computer vision, and deep learning.
o Support for domain-specific applications like medical image analysis,
sentiment analysis, and IoT data processing.

4. Faculty Guidance and Mentorship:
o Expert faculty and mentors to guide students through complex algorithms and
project implementation.
o Workshops and training sessions on the latest trends and advancements in
machine learning.

5. Generative AI Tools and Frameworks:
o Access to cloud-based AI platforms for scalable model development.
o Libraries like TensorFlow and PyTorch for building generative models.
o Access to pre-trained models like GPT.