Applied Supervised Learning with Python

This course provides you a rich understanding of machine learning, one of the most pursued topics in information science, and Python, one of the most popular scripting languages. Through this course, you'll learn Jupyter Notebooks, the technology used in academic and commercial circles with in-line code running support.

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Learning Objectives

After completing this course, you will be able to:

  • Understand the concept of supervised learning and its applications
  • Implement common supervised learning algorithms using machine learning Python libraries
  • Validate models using the k-fold technique
  • Build your models with decision trees to get results effortlessly
  • Use ensemble modeling techniques to improve the performance of your model
  • Apply a variety of metrics to compare machine learning models

 

Course Details

Course Outline

1 - Python Machine Learning Toolkit
  • Supervised Machine Learning
  • Jupyter Notebooks
  • pandas
  • Data Quality Considerations
  • 2 - Exploratory Data Analysis and Visualization
  • Summary Statistics and Central Values
  • Missing Values
  • Distribution of Values
  • Relationships within the Data
  • 3 - Regression Analysis
  • Regression and Classification Problems
  • Linear Regression
  • Multiple Linear Regression
  • Autoregression Models
  • 4 - Classification
  • Linear Regression as a Classifier
  • Logistic Regression
  • Classification Using K-Nearest Neighbors
  • Classification Using Decision Trees
  • 5 - Ensemble Modeling
  • Overfitting and Underfitting
  • Bagging
  • Boosting
  • 6 - Model Evaluation
  • Evaluation Metrics
  • Splitting the Dataset
  • Performance Improvement Tactics
  • Actual course outline may vary depending on offering center. Contact your sales representative for more information.

    Who is it For?

    Target Audience

    Applied Supervised Learning with Python is for you if you want to gain a solid understanding of machine learning using Python. It'll help if you have some experience in any functional or object-oriented language and a basic understanding of Python libraries and expressions, such as arrays and dictionaries.

    Applied Supervised Learning with Python

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    Course Length : 2 Days (16 Hours)

    There are currently no scheduled dates for this course. Please contact us for more information.

    Need Help Picking the Right Course? Give us a call! 901-375-1533