Deep Learning Workshop (Virtual) with Meta PyTorch – February 18, 2023
For students and professionals to understand the basics and impact of Deep Learning in today’s world
Deep Learning Workshop Series
- 2018 – Defect Detection in Biopharmaceuticals
- Model Thesis: Amgen – Nyovanie ’19
- Sponsor: AWS
- Key Learnings : Cloud-based training with Edge-based inference
- 2019 – False Positive Rejection in PCB Assembly
- Model Thesis: FLEX – Foster ’19
- Sponsors: NVIDIA, AWS
- Key Learnings: Data Curation; Model performance comparison; Data pipelining
- 2020 – Expand to two-day virtual session
- False Positive Rejection in PCB Assembly (above) – 1 day
- LGO Alumni Machine Intelligence Use Case review – 1 Day
- Key learnings: Broader view of types of problems solved with MI, range of approaches and their applicability, implementation best practices
- 2021 – 3rd Annual MIT MIMO Deep Learning Workshop
- Prof. Duane Boning – Time-series analysis comparison in plasma etch – MLP vs. LSTM RNN vs. Clustering
- Prof. Retsef Levi – Time-series analysis comparison BMW Brake noise classification CNN vs. LSTM
- Dr. Brian Anthony PRS – Time-series analysis applied to video based condition-monitoring
- Sang Woon Kim PhD Candidate – Applied deep reinforcement to real-time control
- Kerry Weinberg LGO ’16 – Director Data Science, Amgen – Bone density prediction using time-series data
- Dr. Chris Couch PhD ’98 – CTO Cooper Standard – Machine Learning Real Time Process Control
- Mahendra Bairagi – AWS Solutions Architect – Time Series Predictive Maintenance
- 2022 – A Non-Mathy Deep Learning Workshop