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ChatGPT for Data Science and Machine Learning

سرفصل های دوره

Beginner and advanced chatGPT use cases - hypothesis testing, supervised learning, Naive Bayes, ethics in AI


1. Introduction to the data science process and chatGPT
  • 1. Introduction
  • 2. Traditional data science methods and the role of ChatGPT
  • 3. How to install chatGPT
  • 4. How ChatGPT can boost your productivity

  • 2. Data science use cases
  • 1.1 data preprocessing medical data.zip
  • 1.2 patients.csv
  • 1. Data preprocessing with ChatGPT
  • 2.1 diagnosis mapping.csv
  • 2.2 medical data ml attempt.zip
  • 2.3 patients preprocessed.csv
  • 2. First attempt at machine learning with ChatGPT
  • 3.1 customers.csv
  • 3.2 orders.csv
  • 3.3 products.csv
  • 3.4 ratings.csv
  • 3. Analyzing a client database with ChatGPT in Python
  • 4. Analyzing a client database with ChatGPT in Python analyzing top products
  • 5.1 furniture store data analysis.zip
  • 5. Analyzing a client database with ChatGPT in Python analyzing top clients, RFM
  • 6.1 properties.csv
  • 6. Exploratory data analysis (EDA) with ChatGPT - histogram and scatter plot
  • 7.1 properties analysis.zip
  • 7. Exploratory data analysis (EDA) with ChatGPT - correlation matrix, outlier detec
  • 8. Assignment 1.html
  • 9.1 students hypothesis testing.zip
  • 9.2 students.csv
  • 9. Hypothesis testing with ChatGPT
  • 10.1 Marvel Comics.zip
  • 10. Marvels comic book database Intro to Regular Expressions (RegEx)
  • 11.1 marvel comics reg ex.zip
  • 11. Decoding comic book data Python Regular Expressions and ChatGPT
  • 12. Assignment 3.html
  • 13.1 movies metadata.zip
  • 13.2 ratings small.csv
  • 13. Algorithm recommendation Movie Database Analysis with ChatGPT
  • 14. Algorithm recommendation recommendation engine for movies with ChatGPT
  • 15. Assignment 4.html
  • 16. Ethical principles in data and AI utilization
  • 17.1 friendships.csv
  • 17.2 interactions.csv
  • 17.3 posts.csv
  • 17.4 users.csv
  • 17. Using ChatGPT for ethical considerations

  • 3. Intro to the case study
  • 1. Intro to the case study
  • 2.Naive Bayes
  • 3. Tokenization and Vectorization
  • 4. Imbalanced data sets
  • 5. Overcome imbalanced data in machine learning
  • 6. Model performance metrics

  • 4. Case study of user reviews and sentiment analysis
  • 1.1 user courses review 09 2023.csv
  • 1. Loading the Dataset and Preprocessing
  • 2. Optimizing user reviews data preprocessing & EDA
  • 3. Reg Ex for Analyzing Text Review Data
  • 4. Understanding Differences between Multinomial and Bernouilli Naive Bayes
  • 5. Machine learning with Naive Bayes (first attempt)
  • 6.1 365 user reviews naive bayes sentiment analysis.zip
  • 6. Machine learning with Naive Bayes converting the problem to a binary one
  • 7.1 user courses review test set.csv
  • 7. Testing the model on new data
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    تاریخ انتشار: 25 اردیبهشت 1403
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