Hands-on learning materials for the NVIDIA Deep Learning Institute (DLI) course: Fundamentals of Deep Learning—covering computer vision and NLP through interactive labs.

• Jupyter notebooks and code examples
• Slides & lecture notes
• Hands-on lab exercises
• Final project implementations

(All based strictly on the DLI workshop—no extra content.)

Aligned with the official workshop outline (total 8 hrs):

1. Introduction (15 min)

   • Meet instructor
   • Create account at courses.nvidia.com/join

2. The Mechanics of Deep Learning (120 min)

   • Train first computer vision model
   • Use CNNs to improve vision accuracy
   • Apply data augmentation

3. Pre-trained Models & Recurrent Networks (120 min)

   • Integrate image‑classification pre-trained models
   • Transfer learn for personalized applications
   • Train RNN to autocomplete text based on NYT headlines

4. Final Project: Object Classification (120 min)

   • Classify fresh vs rotten fruit from color images
   • Build data generators for small datasets
   • Combine transfer learning + feature extraction
   • Discuss advanced architectures & research directions

5. Final Review (15 min)

   • Review key learnings
   • Assessment & certification
   • Workshop survey
   • Setup your own AI development environment

• Experience with Python 3 (functions, loops, arrays, dictionaries)
• Familiarity with Pandas
• Basic understanding of regression & neural networks

• TensorFlow 2 + Keras, PyTorch (where applicable)
• NumPy, Pandas
• GPU‑accelerated notebook server provided by NVIDIA

By completing this workshop, you'll:

• Understand training workflows for vision and sequential data
• Effectively apply CNNs, RNNs, data augmentation, transfer learning
• Build your own deep learning development environment
• Earn an NVIDIA DLI certification upon passing the final assessment

1. Clone this repo
2. Sign up at courses.nvidia.com/join
3. Launch Jupyter notebooks in the provided environment
4. Complete labs in this order:
   • Mechanics of DL
   • Pre-trained & RNN
   • Final Project
   • Assessment & Review

All content complies with NVIDIA DLI's educational usage terms.