OCJP

Data Analysis using Python

Module 1 – Importing Datasets

  • Learning Objectives
  • Understanding the Domain
  • Understanding the Dataset
  • Python package for data science
  • Importing and Exporting Data in Python
  • Basic Insights from Datasets

Module 2 – Cleaning and Preparing the Data

  • Identify and Handle Missing Values
  • Data Formatting
  • Data Normalization Sets
  • Binning
  • Indicator variables

Module 3 – Summarizing the Data Frame

  • Descriptive Statistics
  • Basic of Grouping
  • ANOVA
  • Correlation
  • More on Correlation

Module 4 – Model Development

  • Simple and Multiple Linear Regression
  • Model Evaluation Using Visualization
  • Polynomial Regression and Pipelines
  • R-squared and MSE for In-Sample Evaluation
  • Prediction and Decision Making

Module 5 – Model Evaluation

  • Model  Evaluation
  • Over-fitting, Under-fitting and Model Selection
  • Ridge Regression
  • Grid Search
  • Model Refinement

Leave a Reply

Your email address will not be published. Required fields are marked *


× How can I help you?