Python
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  • Introduction
  • Chapter 1.Notes from research
  • Chapter 2.Courses
    • 2.1.Python for Data Science and Machine Learning Bootcamp
      • 2.1.1.Virtual Environment
      • 2.1.2.Python crash course
      • 2.1.3.Python for Data Analysis - NumPy
      • 2.1.4.Python for Data Analysis - Pandas
      • 2.1.5.Python for Data Visual Visualization - Pandas Built-in Data Visualization
      • 2.1.6.Python for Data Visualization - Matplotlib
      • 2.1.7.Python for Data Visualization - Seaborn
      • 2.1.8. Python for Data Visualization - Plotly and Cufflinks
      • 2.1.9. Python for Data Visualization - Geographical plotting
      • 2.1.10.Combine data analysis and visualization to tackle real world data sets
      • 2.1.11.Linear regression
      • 2.1.12.Logistic regression
      • 2.1.13.K Nearest Neighbors
      • 2.1.14.Decision trees and random forests
      • 2.1.15.Support Vector Machines
      • 2.1.16.K means clustering
      • 2.1.17.Principal Component Analysis
    • 2.2. Machine Learning Crash Course Jam
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  1. Chapter 2.Courses
  2. 2.1.Python for Data Science and Machine Learning Bootcamp

2.1.15.Support Vector Machines

  • Please refer to this article

Previous2.1.14.2.Decision trees and Random Forests with PythonNext2.1.16.K means clustering

Last updated 5 years ago

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