Analytics-University
The video discusses the use of Chat GPT for running logistic regressions in Python. Chat GPT provides precise answers to user queries, saving more time compared to searching on Google. The speaker demonstrates how Chat GPT can be used for running stepwise logistic regressions using stats model, SQL, and SK learn. It can also aid in the development of confusion matrix calculations and data frame creation. Overall, Chat GPT is a useful tool for data scientists looking to save time and obtain specific answers to their problems.
In this section, the speaker discusses how Chat GPT can be used to run logistic regressions in Python. Chat GPT provides specific answers to users' questions and can save a lot of time compared to searching on Google. The speaker demonstrates how Chat GPT can be used to run stepwise logistic regressions using stats model and how it can also provide solutions for SQL and SK learn. Additionally, the speaker explains that Chat GPT can help with other tasks such as confusion matrix calculations and data frame creation. Overall, Chat GPT is a useful tool for data scientists to save time and get specific answers to their questions.
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