NLP Project Lifecycle - From Data Labelling to Deployment Ft. Gagandeep Singh (Zykrr)

Опубликовано: 27 Май 2024
на канале: ProjectPro - Data Science Projects

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Natural Language Processing has made remarkable strides in recent years. With the advent of large language models like GPT, the field is witnessing a paradigm shift. From data labeling to model deployment, NLP is revolutionized by cutting-edge techniques and novel approaches. NLP is revolutionizing how we interact with machines, from advanced language models like GPT-4 to powerful translation, summarization, and sentiment analysis tools. In this episode of "ProjectPro Industry Talks," our Co-founder, Binny Mathews, converses with Gagandeep Singh, an experienced professional with over 5 years of experience in NLP and Data Science and currently a senior data science manager at Zykrr. He shares his insights and best practices from his extensive experience working on NLP projects and discusses the NLP Project life cycle. He discusses strategies for larger production projects, the role of active learning through user feedback in continuously improving models, emerging trends like using GPT models for data labeling, and much more!

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00:00 Introduction
00:55 Essential Queries for Successful NLP Projects
04:06 Data Labeling vs. Resource Allocation Tradeoffs
07:30 The Role of Annotators in NLP
09:01 Scaling NLP Data
11:00 Tuning Word Occurrence for Sentiment Analysis
13:48 Active Learning in Data Labelling
16:16 Resume Parser Example
18:07 Addressing Data Imbalance with Annotation
20:18 Benchmarking NLP Model Output Quality
22:42 Emerging Trends in Data Labelling
24:11 Optimizing NLP Annotations
24:57 Traditional ML Models Vs GPT
26:31 Conclusion