Deep Learning: From Basics to Production
Table of Contents
Course Overview #
This course is designed for everyone from beginners to those looking to apply deep learning in production environments.
Learning Objectives #
- Understand fundamental neural network principles
- Gain proficiency in TensorFlow/PyTorch
- Train and evaluate models with real datasets
- Experience production environment deployment
Course Structure #
Part 1: Fundamental Theory
- Basic neural network architecture
- Backpropagation algorithm
- Optimization techniques
Part 2: Practical Projects
- Image classification with CNN
- Time series prediction with RNN/LSTM
- NLP with Transformer models
Part 3: Deployment & Optimization
- Model optimization
- TensorFlow Serving
- Cloud deployment
Teaching Method #
- Online/Offline: Zoom or in-person sessions
- Hands-on focused: Practical projects every session
- 1:1 Feedback: Personal project code reviews
Target Audience #
- Developers familiar with Python basics
- Those interested in machine learning
- Anyone wanting to apply deep learning in practice
Contact #
For course schedule and pricing inquiries, please reach out via email.