Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

LinkedIn Learning

Python: Working with Predictive Analytics

via LinkedIn Learning

Write review

No Longer Offered

Simplilearn Ad

Earn a Michigan Engineering AI Certificate — Stay Ahead of the AI Revolution

Learn More → Coursera Ad

Learn AI, Data Science & Business — Earn Certificates That Get You Hired

Learn More →

Overview

Build a Learning Habit
Download Class Central's free printable study calendar
Download for Free
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 615 ratings

Start your review of Python: Working with Predictive Analytics

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free
Someone learning on their laptop while sitting on the floor.