Predictive Analytics Table of Content

Table of Content

Predictive Analytics & Big Data

  • Predictive Analytics and Big Data
  • Predictive Analytics Evolution

Process & Application

  • Applications of Predictive Analytics
  • Predictive Analytics Process and Technology
  • Practice: Identifying the Type of Analytics

Key Statistical Concepts

  • Importance of Statistics in Analytics
  • Overview of Probability Theory
  • Using Statistics in Predictive Analytics

Correlation & Regression

  • Introduction
  • Practice: Applying Statistical Approaches

Data Collection & Exploration

  • Data Needs and Sources
  • Data Collection and Exploration

Data Mining, Data Distributions, & Hypothesis Testing

  • Data Mining and Analytics
  • Data Distributions and Hypothesis Testing
  • Practice: Data Mining Methods

Data Preprocessing

  • Pre-processing Data

Data Reduction & Exploratory Data Analysis (EDA)

  • Data Reduction with PCA and Factor Analysis
  • Tools for Exploratory Data Analysis (EDA)
  • Practice: Using PCA for Feature Selection

A/B Testing, Bayesian Networks, and Support Vector Machine

  • A/B Testing
  • Naïve Bayes and Bayesian Belief Networks
  • Support Vector Machines
  • Practice: Applying Predictive Approaches

Artificial Neural Networks

  • K-Nearest Neighbor (k-NN)
  • K-Nearest Neighbor (k-NN) & Artificial Neural Networks

Clustering Techniques

  • Using Clustering Techniques
  • K-Means Clustering
  • Hierarchical Clustering and DBSCAN

Linear and Logical Regression

  • Linear Regression
  • Logistic Regression
  • Practice: Linear Regression Inference

Text Mining & Social Network Analysis

  • Text Mining
  • Social Network and Media Analytics

Time Series Modeling

  • Introduction to Time Series
  • Time Series Forecasting Models
  • Practice: Time Series Modeling Concepts

Machine Learning, Propensity Score, & Segmentation Modeling

  • Machine Learning
  • Propensity Score and Segmentation Modeling

Random Forests & Uplift Models

  • Random Forests
  • Uplift Models
  • Practice: Advanced Predictive Tools

Model Life Cycle Management

  • Introducing Model Life Cycle Management

Model Development, Validation, & Evaluation

  • Model Building
  • Model Considerations and Validation
  • Model Evaluation
  • Practice: Classification Model Performance

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