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LinkedIn Learning

Python: Working with Predictive Analytics (2019)

via LinkedIn Learning

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Overview

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Find out how to use prebuilt Python libraries for predictive analytics and discover insights about the future.

Syllabus

Introduction
  • Predict data in Python
  • Road map
1. Data Preprocessing
  • Differentiate data types
  • Python libraries and data import
  • Handling missing values
  • Convert categorical data into numbers
  • Divide the data into test and train
  • Feature scaling
2. Prediction Models
  • Introduction to predictive models
  • Linear regression
  • Polynomial regression
  • Support Vector Regression (SVR)
  • Decision tree regression
  • Random forest regression
  • Evaluation of predictive models
  • Hyperparameter optimization
  • Challenge: Hyperparameter optimization
  • Solution: Hyperparameter optimization
Conclusion
  • Next steps

Taught by

Isil Berkun

Reviews

4.6 rating at LinkedIn Learning based on 841 ratings

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