Neural Networks, Transfer Learning, and Visualizing Graphs with TensorFlow
Below are the videos from the Boston TensorFlow meetup—sponsored and organized by Altoros on March 7, 2016.
Talk #1: Neural Networks with Google TensorFlow
Talk #2: Transfer learning on TensorFlow in 30 minutes
Syed Tousif Ahmed of Alhold USA provided answers for the following questions:
- What is transfer learning (strategies, use cases)?
- How to collect data?
- How to retrain a model in TensorFlow?
Later on, Renat Khasanshyn interviewed Darshan Patel and Syed Tousif Ahmed on the following aspects:
- What does attract you most in TensorFlow?
- How can TensorFlow make a difference as a library in the next 5–10 years?
- Pieces of advice for those getting started with TensorFlow
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- Visualizing TensorFlow Graphs with TensorBoard
- What Is Behind Deep Reinforcement Learning and Transfer Learning with TensorFlow?
- Image and Text Recognition with TensorFlow Using Convolutional Neural Networks
About the experts
Darshan Patel is a machine learning enthusiast. He is in his second year of Computer Science Masters in the College of Computer and Information science at Northeastern University. Prior to a master study, Darshan was a software developer at TCS, India.
Syed Tousif Ahmed is a Computer Vision Developer working at Ahold USA. He is also a student in Computer Engineering at Rochester Institute of Technology. Syed’s area of interests are computer vision, machine learning, cryptography, and Internet of Things.