An Active Learning Framework to Optimize Model Training

Event Information

Share this event

Date and Time

Location

Location

Magnimind Academy

830 Stewart Dr, #182

Sunnyvale, CA 94085

View Map

Event description
Explore different ways to optimize the selection of training data quickly and cost-effectively and improve the performance of a deep model

About this Event

Deep learning models have been used extensively to solve real-world problems in recent years. The performance of such models relies heavily on large amounts of labeled data for training. While the advances of data collection technology have enabled the acquisition of a massive volume of data, labeling the data remains an expensive and time-consuming task. Active learning techniques are being progressively adopted to accelerate the development of machine learning solutions by allowing the model to query the data they learn from.

In this talk, we introduce a real-world problem, the recognition of parking signs, and present a framework that combines active learning techniques with a transfer learning approach and crowd-sourcing tools to create and train a machine learning solution to the problem.

We discuss how such a framework contributes to building an accurate model in a cost-effective and fast way to solve the parking sign recognition problem in spite of the unevenness of the data associated with the fact that street-level images (such as parking signs) vary in shape, color, orientation and scale, and often appear on top of different types of background.

Agenda:

6:20 pm - 6:30 pm Arrival and socializing

6:30 pm - 6:40 pm Opening words

6:40 pm - 7:50 pm Humayun Irshad, "An Active Learning Framework to Optimize Model Training"

7:50 pm - 8:00 pm Q&A

About Humayun Irshad:

Humayun Irshad is currently the Lead Scientist of Machine Learning at Figure Eight, the essential human-in-the-loop AI platform for data science and machine learning teams. He has expertise in developing machine learning, more specifically deep learning frameworks for various applications like object detection, segmentation and classification in fields ranging from medical, retail, self-driving car, satellite, fashion, etc. Now a days, he is building Active Learning frameworks for selection of training data from labeled or unlabeled dataset to build model to avoid over-training and dealing corner cases. He has 3 years PostDoc experience at Harvard Medical School where he developed machine learning and deep learning frameworks for Computer Aided Diagnosis system including region of interest detection, nuclei and gland detection, segmentation and classification in 2D and 3D medical images. He got a PhD in Computer Science from University of Grenoble France.

A computer scientist with expertise’s in machine learning, deep learning, computer vision, bio-medical image analysis and statistical methods. He likes to use his analytical mind not only when building complex models, but also as part of his leadership philosophy. Humayun also enjoys sharing his experiences in technical and non-technical audiences in conferences, seminars and meetings.

Date and Time

Location

Magnimind Academy

830 Stewart Dr, #182

Sunnyvale, CA 94085

View Map

Save This Event

Event Saved