Human in the Loop Machine Learning: What a Veteran Data Scientist Wishes You Knew

Uncover the significance of human involvement in refining machine learning models and ensuring optimal outcomes. Enhance your understanding of this dynamic intersection between human intelligence and machine capabilities.

Sections of the Video
[00:00] Introduction
[08:32] Understanding "Human in the Loop" in Machine Learning
[10:01] The Role of Deep Learning
[16:26] Supervised Learning vs. Reinforcement Learning
[24:54] Exception Processing in Machine Learning
[31:13] Google's Human-Powered Refinement:
[32:22] Human Insight in Natural Language Processing:
[33:56] Benefits of Human Involvement in Machine Learning:
[34:59] Challenges in Optical Character Recognition (OCR):
[36:39] Active Learning and Human Loop Routing:
[38:45] Ethical Considerations and Cloud Factory's Approach:
[39:22] Lack of Awareness on Human in the Loop:
[40:51] Education Gap in Data Science Programs:
[46:50] Expertise Development in Data Annotation:
[48:28] Future Applications of Human in the Loop:
[1:01:11] Human in the Loop and Deep Fakes:
[1:01:47] System Triggers for Human Intervention:
[1:03:34] Quality Control and Mislabelled Data:
[1:05:16] Selecting the Best Question:
[1:07:02] Conclusion and Appreciation:
[1:08:12] Contact Information and Resources:
[1:09:15] Closing Remarks and Preview of Next Session:

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