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The Role of ChatGPT in Data Science: How AI-Assisted Conversational Interfaces Are Revolutionizing the Field

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Izdano u:Big Data and Cognitive Computing vol. 7, no. 2 (2023), p. 62
Glavni autor: Hassani, Hossein
Daljnji autori: Silva, Emmanuel Sirmal
Izdano:
MDPI AG
Teme:
OpenAI
Language
Text categorization
Scientists
Deep learning
Trends
Chatbots
Machine learning
Workflow
Data science
Plagiarism
Privacy
Decision making
Language translation
Algorithms
Training
Big Data
Decision analysis
Data mining
Artificial intelligence
Sentiment analysis
Neural networks
Natural language processing
Unstructured data
Synthetic data
Conversation
Conversational artificial intelligence
Classification
Cleaning
Data
Language acquisition
Data processing
Interfaces
Intelligence
Productivity
Translation
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Sažetak:ChatGPT, a conversational AI interface that utilizes natural language processing and machine learning algorithms, is taking the world by storm and is the buzzword across many sectors today. Given the likely impact of this model on data science, through this perspective article, we seek to provide an overview of the potential opportunities and challenges associated with using ChatGPT in data science, provide readers with a snapshot of its advantages, and stimulate interest in its use for data science projects. The paper discusses how ChatGPT can assist data scientists in automating various aspects of their workflow, including data cleaning and preprocessing, model training, and result interpretation. It also highlights how ChatGPT has the potential to provide new insights and improve decision-making processes by analyzing unstructured data. We then examine the advantages of ChatGPT’s architecture, including its ability to be fine-tuned for a wide range of language-related tasks and generate synthetic data. Limitations and issues are also addressed, particularly around concerns about bias and plagiarism when using ChatGPT. Overall, the paper concludes that the benefits outweigh the costs and ChatGPT has the potential to greatly enhance the productivity and accuracy of data science workflows and is likely to become an increasingly important tool for intelligence augmentation in the field of data science. ChatGPT can assist with a wide range of natural language processing tasks in data science, including language translation, sentiment analysis, and text classification. However, while ChatGPT can save time and resources compared to training a model from scratch, and can be fine-tuned for specific use cases, it may not perform well on certain tasks if it has not been specifically trained for them. Additionally, the output of ChatGPT may be difficult to interpret, which could pose challenges for decision-making in data science applications.
ISSN:2504-2289
Digitalni identifikator objekta:10.3390/bdcc7020062
Izvor:Advanced Technologies & Aerospace Database