TensorFlow projects for B.Tech students — real examples

What students actually build

• Vision and prediction capstone projects at VSET are frequently built with TensorFlow or Keras.
• Hackathon teams use it where a pretrained model can be adapted quickly to a problem statement.

Labs and infrastructure

• The AICTE IDEA Lab provides GPU workstations for training and evaluating models on campus.
• IDEA Lab embedded hardware supports students taking models towards on-device inference.

How VSET teaches TensorFlow

TensorFlow is a deep learning framework for building, training and deploying neural networks, with Keras as its high-level modelling interface and strong support for production serving. It is working tooling inside the machine learning coursework of the CSE AI and ML specialisation at VSET. At VSET this maps to documented coursework depth inside B.Tech CSE (AI & ML).

• VSET offers B.Tech CSE with an AI and Machine Learning specialisation among its seven GGSIPU programmes.
• Machine learning and deep learning coursework there uses Python frameworks including TensorFlow and Keras.
• Linear algebra, calculus and probability coursework supply the mathematics behind the framework operations.
• Deployment of trained models connects to the cloud computing coursework in the CSE track.