Current Trends in Machine Learning & Deep Learning
About this webinar
This webinar in the Deep Learning (DL) series presented by an industry expert Sylvain Flamant, he will
give a deeper understanding of the current industry trends in DL and ML. This webinar will give you an
insight about how the ML industry is developing at a rapid pace and how the hardware and the software
stack is evolving continuously. This webinar is ideal for AI enthusiasts who wanted to understand how
End-To-End AI applications are built by large Enterprises/businesses using the state-of-the-art
infrastructure to develop the models.
Takeaways
• State-of-the-art technology stack used in AI model development.
• Current trends in AI hardware & software development.
• Most widely used tools for DL model development & deployment.
• Roadmap of AI development in the next 5 years.
• Current trends in AI hardware & software development.
• Most widely used tools for DL model development & deployment.
• Roadmap of AI development in the next 5 years.
Preparation
● This webinar will be completely online on zoom. Please make sure to download the zoom
application on your laptop or mobile / Tablet.
● We will provide the zoom link before the webinar.
● We will provide the zoom link before the webinar.
About the instructor
Sylvain Flamant
Sylvain obtained a 5-year Engineering degree in mechanics and optics at ENSMM in France. He served 17 months in Germany as an officer in the French army. He later earned an MSEE degree (1984) in signal processing and communications at Stanford University. Sylvain then put his DSP and telecom skills to good use, working as a DSP Engineer at Anritsu and Ikanos. His immense DSP skills landed him for the opportunity to work at At Wave Computing, where he was part of the Machine Learning core group, to implement and simulate ML models and to confirm the performance of the models on Wave Computing hardware using fixed-point and floating-point proprietary hardware data-types. He has patents multiple filed with his name ranging from DSP to ML modeling on different hardware. His area of expertise lies in:
- DSP
- Deep Learning
- ML Optimization & Quantization