Transfer Learning with PyTorch: Theory & 3 Projects https://WebToolTip.com Published 7/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 6h 26m | Size: 2.09 GB
Understand concepts, compare CNN and NLP models, fine-tune and evaluate, and develop 3 practical AI projects.
What you'll learn
understand fundamentals of Transfer learning and why it is widely used in modern AI applications
understand the difference between traditional deep learning and modern transfer learning approaches
3 hands on projects in computer vision, NLP, Speech recognition with elaborated fine tuning methods to understand about evaluation metrics better
detailed explanation of code with possible range of values that can be given to each parameter
students can confidently explain the theory behind Transfer learning
effectively fine-tune pretrained models to improve prediction accuracy.
identify the project shortcomings and tune the project better.
those 3 project uses more than two transfer learning models and traditional ML approach to compare better performance.
Requirements
knowledge of python programming language upto object oriented programming. basic understanding of AI model understanding and is optional as basic architecture is explained briefly. tools needed: google colab notebook, visual studio code for projects.