
Darryl Fernandes
Senior Machine Learning Engineer
This course equips learners with essential techniques to enhance machine learning models. Starting with an introductory overview, the course covers key optimization strategies, including quantization techniques that reduce model size and improve efficiency. Students will explore pruning and sparsity methods to eliminate redundancy in models. The use of profiling tools and performance analysis is emphasized, allowing students to assess and refine their models effectively. Finally, the course culminates in practical applications, featuring hands-on experience with optimizing and deploying the GPT-2 model. Students will gain a solid foundation in optimizing state-of-the-art models for real-world applications.

Subscription · Monthly
2 skills
3 prerequisites
Prior to enrolling, you should have the following knowledge:
You will also need to be able to communicate fluently and professionally in written and spoken English.
1 instructor
Unlike typical professors, our instructors come from Fortune 500 and Global 2000 companies and have demonstrated leadership and expertise in their professions:

Darryl Fernandes
Senior Machine Learning Engineer
Learn to boost machine learning model speed and efficiency using pruning, quantization, and profiling tools like TensorBoard and PyTorch Profiler to find bottlenecks.

Subscription · Monthly