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Hands-on Machine Learning in Python & ChatGPT

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Hands-on Machine Learning Tutorial with Pandas, Numpy, Seaborn, Scikit-learn in Python and ChatGPT: A Complete Work-flow


1. Setting Up Your Data Analysis Platform
  • 1.1 Mac.pdf
  • 1.2 Windows.pdf
  • 1. Install Python and Jupyter Notebook.html
  • 2.1 Instructions of setting up ChatGPT.pdf
  • 2. Setting Up ChatGPT for Easy Machine Learning.html

  • 2. What is Machine Learning
  • 1. Machine Learning and Its Characteristics
  • 2. Complete Machine Learning Work-flow
  • 3.1 Practice datasets.zip
  • 3. Practice datasets.html
  • 4. Instructions for Quizzes IMPORTANT.html

  • 3. Master Data Cleaning for Error-free ML Model
  • 1. Load your dataset into Python environment
  • 2. Handling missing values with Scikit-learn
  • 3. Identify and deal with inconsistent data
  • 4. Dealing with miss-identified data types
  • 5. Address and remove duplicated data
  • 6. QUIZ 1 Data Cleaning.html
  • 7.1 data cleaning (solution).zip
  • 7. Solution 1 Data Cleaning.html

  • 4. Master Data Manipulation for Strong ML Model
  • 1. Sorting and arranging dataset
  • 2. Filter data based on conditions
  • 3. Merging or adding of supplementary variables
  • 4. Concatenating or adding of supplementary data
  • 5. QUIZ 2 Data Manipulation.html
  • 6.1 data manipulation (solution).zip
  • 6. Solution 2 Data Manipulation.html

  • 5. Master Data Preprocessing for Perfect ML Model
  • 1. Feature engineering Generating new data
  • 2. Extracting day, months, year from date variable
  • 3. Feature encoding Assigning numeric values
  • 4. Creating dummy variables for nominal data
  • 5. Data standardizing and normalizing with StandardScaler
  • 6. Splitting data into training and testing set
  • 7. QUIZ 3 Data Preprocessing.html
  • 8.1 data preprocessing (solution).zip
  • 8. Solution 3 Data Preprocessing.html

  • 6. Hands-on Machine Learning Application Part 1 Regression
  • 1. Read It IMPORTANT.html
  • 2. Linear regression ML model
  • 3. Decision Tree regression ML model
  • 4. Random Forest regression ML model
  • 5. Support Vector regression ML model
  • 6. XGBoost regression ML model
  • 7. QUIZ 4 ML Model Application Part 1.html
  • 8.1 ml model application part 1 (solution).zip
  • 8. Solution 4 ML Model Application Part 1.html

  • 7. Hands-on Machine Learning Application Part 2 Classification
  • 1. Read It IMPORTANT.html
  • 2. Logistic Regression ML model
  • 3. Decision Tree classification ML model
  • 4. Random Forest classification ML model
  • 5. K Nearest Neighbours classification ML model
  • 6. LightGBM classification ML model
  • 7. QUIZ 5 ML Model Application Part 2.html
  • 8.1 ml model application part 2 (solution).zip
  • 8. Solution 5 ML Model Application Part 2.html

  • 8. Hands-on Machine Learning Application Part 3 Clustering
  • 1. KMeans Clustering ML model
  • 2. Final QUIZ ML Model Application Part 3.html
  • 3.1 fast-track ml in python & chatgpt (solution).zip
  • 3. Final Solution Fast-Track ML in Python & ChatGPT.html

  • 9. Tips, Tricks and Resources
  • 1. ChatGPT Your best code companion
  • 2.1 Complete ML workflow.pptx
  • 2.2 ML.pptx
  • 2. Course resources.html
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    تاریخ انتشار: 27 آذر 1402

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