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Analytics and Types
After watching this video; you will be able to recognize key characteristics and types of analytics.
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Data Mining
After watching this video; you will be able to distinguish between the two aspects of data mining.
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Data Types and Data Preprocessing
After watching this video; you will be able to differentiate between data acquisition and data reduction.
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Finance and Healthcare Applications
After watching this video; you will be able to illustrate a finance and healthcare application of predictive analytics.
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Fraud Detection and Risk Management
After watching this video; you will be able to illustrate a fraud detection or risk management application of predictive analytics.
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Generalized Linear Models
After watching this video; you will be able to define generalized linear model and provide an example of its use.
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Logistic Regression
After watching this video; you will be able to define logistic regression model and provide an example of its use.
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Machine Learning
After watching this video; you will be able to define machine learning models and provide an example of their use.
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Management Decision Support Systems
After watching this video; you will be able to illustrate a management decision support system application of predictive analytics.
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Modeling Tools – Open Source and Commercial
After watching this video; you will be able to name key analytics tools on the market or open-source tools.
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Neural Networks
After watching this video; you will be able to define neural network models and provide an example of their use.
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Models
After watching this video; you will be able to identify common predictive analytics models.
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Overview
After watching this video; you will be able to identify key characteristics and examples of predictive analytics.
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Propensity Modeling
After watching this video; you will be able to define propensity models and provide an example of its use.
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ROI Analysis
After watching this video; you will be able to use predictive analytics to support an ROI decision.
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Sales and Marketing Applications
After watching this video; you will be able to illustrate a sales and marketing application of predictive analytics.
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Statistical Models
After watching this video; you will be able to identify statistical models and provide examples of their use.
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Technology and Big Data Influences
After watching this video; you will be able to recognize technology and big data influences on predictive analytics.
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Times Series Analysis
After watching this video; you will be able to analyze time series data using a common analysis technique.
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Uplift Models
After watching this video; you will be able to define uplift models and provide an example of their use.
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Using a Predictive Modeling Tool
After watching this video; you will be able to perform a simple application of predictive analytics using sample data and a software tool.
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Clustering
After watching this video; you will be able to identify applications of clustering.
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Decision Trees
After watching this video; you will be able to define decision tree model and provide an example of its use.
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Predictive Analytics: Overview of Text Mining
After watching this video, you will be able to identify key characteristic of text mining.
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Predictive Analytics: K-Means Clustering Termination Procedures
After watching this video, you will be able to recognize key steps for the termination of K-Means Clustering iterations.
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Predictive Analytics: Evaluation and Considerations for K-Means Clustering
After watching this video, you will be able to evaluate K-Means Clustering.
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Predictive Analytics: Overview of K-Means Clustering
After watching this video, you will be able to list key features of K-Means Clustering.
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Predictive Analytics: Minimizing SSE of Data Points
After watching this video, you will be able to recognize key steps for reducing the sum of squared errors in K-Means Clustering.
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Predictive Analytics: DBSCAN Attributes
After watching this video, you will be able to identify key attributes for performing DBSCAN.
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Predictive Analytics: Hierarchical Clustering and DBSCAN Overview
After watching this video, you will be able to list key features of Hierarchical Clustering and DBSCAN.
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Predictive Analytics: DBSCAN Operation
After watching this video, you will be able to recognize key steps in DBSCAN.
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Predictive Analytics: Ordinary Least Squares (OLS)
After watching this video, you will be able to determine the OLS parameters.
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Predictive Analytics: Drawing Inferences
After watching this video, you will be able to make regression inferences.
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Predictive Analytics: Linear Regression Overview
After watching this video, you will be able to recognize characteristics of linear regression.
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Predictive Analytics: Sum of Squared Errors
After watching this video, you will be able to calculate sum of squared errors.
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Predictive Analytics: Limitations of Naïve Bayes
After watching this video, you will be able to identify various limitations of Naïve Bayes.
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Predictive Analytics: Bayesian Belief Networks
After watching this video, you will be able to recognize features of Bayesian Belief Networks.
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Predictive Analytics: Naïve Bayes Overview
After watching this video, you will be able to recognize key features of Naïve Bayes.
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Predictive Analytics: Predicting Outcomes with Naïve Bayes
After watching this video, you will be able to calculate the probability of an event occurring with Naïve Bayes.
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Predictive Analytics: Determining the Optimal Hyperplane
After watching this video, you will be able to determine the optimal hyperplane.
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Predictive Analytics: Exercise: Use A/B Testing
After watching this video, you will be able to predict outcomes using A/B testing.
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Predictive Analytics: Support Vector Machines Overview
After watching this video, you will be able to identify features of Support Vector Machines.
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Predictive Analytics: Data Transformation Techniques
After watching this video, you will be able to recognize how to transform linear non-separable data to linear separable data.
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Predictive Analytics: Types of Clustering Techniques
After watching this video, you will be able to identify the different types of clustering.
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Predictive Analytics: Proximity Measures for Clustering
After watching this video, you will be able to calculate proximity.
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Predictive Analytics: Introduction to Clustering
After watching this video, you will be able to recognize characteristics of clustering.
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Predictive Analytics: Overview of A/B Testing
After watching this video, you will be able to recognize what A/B testing is and where it is applicable.
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Predictive Analytics: Autoregressive Models
After watching this video, you will be able to identify features of autoregressive models.
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Predictive Analytics: Moving Average Models
After watching this video, you will be able to identify features of moving average models.
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Predictive Analytics: Stationary and Nonstationary Data Series
After watching this video, you will be able to distinguish between stationary time series and nonstationary time series data.
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Predictive Analytics: Time Series Decomposition
After watching this video, you will be able to recognize the various components of time series data.
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Predictive Analytics: Apply Time Series Modeling Concepts
After watching this video, you will be able to apply time series modeling concepts.
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Predictive Analytics: Machine Learning Overview
After watching this video, you will be able to identify key features of machine learning.
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Predictive Analytics: Autoregressive Moving Average (ARMA) Models
After watching this video, you will be able to identify features of ARMA models.
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Predictive Analytics: Parameterization and Forecasting
After watching this video, you will be able to identify various steps required to make a forecast.
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Predictive Analytics: A/B Testing Features
After watching this video, you will be able to establish an A/B test hypothesis and determine what to test.
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Predictive Analytics: Implementing A/B Testing
After watching this video, you will be able to implement A/B testing for web site optimization.
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Predictive Analytics: Social Network Mapping
After watching this video, you will be able to identify key features of social network mapping.
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Predictive Analytics: Key Terms and Concepts
After watching this video, you will be able to recognize key terms and concepts used in social network and media analysis.
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Predictive Analytics: Assigning Across Document Predictor Variables
After watching this video, you will be able to assign across document predictor variables for text mining.
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Predictive Analytics: Term Frequency and Inverse Document Frequency
After watching this video, you will be able to recognize the use of term frequency and inverse document frequency measures for text mining.
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Predictive Analytics: Assigning within Document Predictor Variables
After watching this video, you will be able to assign within document predictor variables for text mining.
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Predictive Analytics: Text Normalization
After watching this video, you will be able to recognize key methods for text normalization.
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Predictive Analytics: Overview of Social Network Analysis
After watching this video, you will be able to identify key characteristics of social network analysis.
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Predictive Analytics: Ego-centric and Network-centric Analysis
After watching this video, you will be able to distinguish between ego-centric and network-centric analysis.
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Predictive Analytics: Sentiment Analysis
After watching this video, you will be able to identify key characteristics of sentiment analysis.
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Predictive Analytics: Text Mining Applications
After watching this video, you will be able to identify examples of text mining applications.
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Predictive Analytics: Time Series Overview
After watching this video, you will be able to identify key characteristics of time series forecasting.
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Predictive Analytics: Considerations for Model Performance
After watching this video, you will be able to identify key considerations of model validation.
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Predictive Analytics: Data Cleaning and Preparation
After watching this video, you will be able to recognize important aspects of data preparation for model development.
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Predictive Analytics: Data Pre-processing and Model Building
After watching this video, you will be able to identify key functions in the model creation process.
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Predictive Analytics: Descriptive Model Evaluation
After watching this video, you will be able to recognize key features of Occam's Razor.
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Predictive Analytics: Mean Squared Error Measures for Prediction
After watching this video, you will be able to calculate mean squared error measures.
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Predictive Analytics: Model Complexity and Resampling
After watching this video, you will be able to balance model complexity with overfitting.
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Predictive Analytics: Model Validation
After watching this video, you will be able to identify features of two-fold validation.
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Predictive Analytics: Lift and Gain Charts
After watching this video, you will be able to interpret lift and gain charts.
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Predictive Analytics: ROC and AUC
After watching this video, you will be able to interpret ROC curves and AUC.
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Predictive Analytics: Variation Measures for Prediction
After watching this video, you will be able to recognize prediction variation measures.
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Predictive Analytics: Evaluating Classification Models
After watching this video, you will be able to recognize evaluation measures for classification models.
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Predictive Analytics: Advanced Predictive Tools
After watching this video, you will be able to implement a random forest and an uplift model using an example dataset.
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Predictive Analytics: Understanding Business Objectives and Data
After watching this video, you will be able to identify key aspects for understanding the business problem and securing the right data.
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Predictive Analytics: Targeting with Uplift Models
After watching this video, you will be able to recognize who to target with uplift models.
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Predictive Analytics: How Uplift Models Work
After watching this video, you will be able to recognize how uplift models work.
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Predictive Analytics: Model Deployment Planning
After watching this video, you will be able to recognize the high-level activities and planning for model deployment.
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Predictive Analytics: Stakeholder Management
After watching this video, you will be able to identify important aspects of stakeholder management.
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Predictive Analytics: Model Development and Deployment
After watching this video, you will be able to recognize best practices for creating and deploying the forecasting model.
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Predictive Analytics: Business Validation and Benchmarks
After watching this video, you will be able to recognize the importance of business validation and the various types of benchmarks to assess the forecasting model project.
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Predictive Analytics: Model Building Process and Data Discovery
After watching this video, you will be able to recognize key phases in developing a model.
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Predictive Analytics: User Training and Model Documentation
After watching this video, you will be able to recognize the best practices for training users and developing project documentation.
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Predictive Analytics: Model Recalibration and Maintenance
After watching this video, you will be able to recognize the importance of monitoring and recalibrating the forecasting model.
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Predictive Analytics: Estimating Treatment Effects
After watching this video, you will be able to estimate treatment effects.
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Predictive Analytics: Example of Propensity Score Matching
After watching this video, you will be able to apply propensity score matching.
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Predictive Analytics: Propensity Score
After watching this video, you will be able to recognize key features of the propensity score.
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Predictive Analytics: Propensity Score Matching
After watching this video, you will be able to identify key features of propensity score matching.
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Predictive Analytics: Overview of Segmentation Modeling
After watching this video, you will be able to identify key features of segmentation modeling.
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Predictive Analytics: EDA and Cluster Segmentation Modeling
After watching this video, you will be able to distinguish between exploratory data analysis and cluster segmentations.
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Predictive Analytics: Random Forest Overview
After watching this video, you will be able to identify key features of random forests.
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Predictive Analytics: Random Forest Model Concepts
After watching this video, you will be able to identify key random forest model concepts.
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Predictive Analytics: Overview of Uplift Models
After watching this video, you will be able to identify key features of uplift models.
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Predictive Analytics: Decision Tree Characteristics
After watching this video, you will be able to identify key features of decision trees.
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Predictive Analytics: Random Forest Model Error Measurement
After watching this video, you will be able to recognize random forest performance measurements.
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Predictive Analytics: Interpreting Results and Testing Significance
After watching this video, you will be able to interpret logistic regression results.
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Predictive Analytics: Odds Ratio and Relative Risk
After watching this video, you will be able to calculate the odds ratio.
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Predictive Analytics: Logistic Regression Overview
After watching this video, you will be able to list key features of logistic regression.
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Predictive Analytics: Logit Transformation and the Likelihood Function
After watching this video, you will be able to recognize the logit transformation and likelihood functions.
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Predictive Analytics: Considerations for Logistic Regression
After watching this video, you will be able to recognize key considerations for logistic regression.
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Predictive Analytics: Linear Regression Statistical Inference
After watching this video, you will be able to determine and interpret the statistical significance of individual variables and of the overall model.
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Predictive Analytics: Machine Learning Tools and Process
After watching this video, you will be able to identify key tools used for machine learning and the high-level process steps.
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Predictive Analytics: Ensemble Techniques for Machine Learning
After watching this video, you will be able to identify key features of ensemble techniques.
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Predictive Analytics: Ensemble Performance Considerations and Metrics
After watching this video, you will be able to measure ensemble error rate.
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Predictive Analytics: Deep Learning
After watching this video, you will be able to identify key features of deep learning.
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Predictive Analytics: Supervised vs. Unsupervised Methods
After watching this video, you will be able to distinguish between supervised and nonsupervised learning methods.
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Predictive Analytics: Interpret Scatter Plots
After watching this video, you will be able to recognize the direction, form, and strength of a scatter plot.
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Predictive Analytics: Wrapper Data Reduction Method
After watching this video, you will be able to recognize key features of the wrapper data reduction method.
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Predictive Analytics: Factor Analysis
After watching this video, you will be able to recognize the key features of factor analysis.
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Predictive Analytics: Information Theory Approach to Feature Selection
After watching this video, you will be able to use the information theory approach for feature selection.
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Predictive Analytics: Chi-square Feature Selection Method
After watching this video, you will be able to recognize the key features of using Chi-square.
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Predictive Analytics: Run Charts and Scatter Plots
After watching this video, you will be able to use run charts and scatter plots to perform EDA.
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Predictive Analytics: Histograms and Stem-and-leaf Plots
After watching this video, you will be able to use histograms and stem-and-leaf plots to perform EDA.
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Predictive Analytics: Overview of EDA and Quantitative Techniques
After watching this video, you will be able to recognize key features of EDA and how quantitative techniques are used to perform EDA.
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Predictive Analytics: Bar Charts and Box-and-whisker Plots
After watching this video, you will be able to use bar charts and box-and-whisker plots to perform EDA.
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Predictive Analytics: Imputation for Continuous Data
After watching this video, you will be able to use imputation to replace missing data.
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Predictive Analytics: Dimension Reduction
After watching this video, you will be able to recognize key data reduction methodologies.
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Predictive Analytics: The Need to Clean Messy Data
After watching this video, you will be able to recognize what is tidy and what is untidy data.
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Predictive Analytics: Outlier Identification and Handling
After watching this video, you will be able to identify outliers and determine whether to remove these values.
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Predictive Analytics: Dummy Variables and Variable Removal
After watching this video, you will be able to recognize important aspects of setting dummy variables and removing variables.
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Predictive Analytics: Approaches for Handling Missing Data
After watching this video, you will be able to recognize key approaches for handling missing data.
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Predictive Analytics: Transforming, Normalizing, and Scaling Data
After watching this video, you will be able to perform data transformation, normalization, and scaling.
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Predictive Analytics: Variable Partitioning
After watching this video, you will be able to recognize important aspects of variable partitioning.
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Predictive Analytics: Principal Component Analysis for Numerical Data
After watching this video, you will be able to use principal component analysis for feature selection.
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Predictive Analytics: Distributions and the Probability Density Function
After watching this video, you will be able to identify features of a standard normal distribution.
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Predictive Analytics: Binomial and Poisson Distributions
After watching this video, you will be able to list features of the Binomial and Poisson distributions.
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Predictive Analytics: Data Mining Concepts and Techniques
After watching this video, you will be able to identify important data mining concepts and techniques.
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Predictive Analytics: Methods for Data Mining
After watching this video, you will be able to identify data mining methods used for predictive analysis.
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Predictive Analytics: One and Two-tailed Hypothesis Tests
After watching this video, you will be able to recognize key features of one and two-tailed hypothesis tests.
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Predictive Analytics: Choose an Appropriate Data Mining Method
After watching this video, you will be able to match analytics problems to appropriate data mining methods.
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Predictive Analytics: Introduction to Hypothesis Testing
After watching this video, you will be able to recognize key features of hypothesis testing and its application.
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Predictive Analytics: Exercise: Evaluate Classification Models
After watching this video, you will be able to determine the superior classification model.
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Predictive Analytics: Other Advanced Predictive Analytics Models
After watching this video, you will be able to identify key features of classification trees, neural networks, support vector machines, and Bayesian networks.
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Predictive Analytics: What is Predictive Analytics?
After watching this video, you will be able to recognize what predictive analytics is, the types of models used, and what its goals are.
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Predictive Analytics: Shedding Light with Predictive Analytics
After watching this video, you will be able to recognize what types of questions are answered by predictive analytics and who uses it.
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Predictive Analytics: Big Data Considerations and Sources
After watching this video, you will be able to recognize the considerations of using big data and what the sources are.
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Predictive Analytics: Time Series, Uplift, and Logistic Models
After watching this video, you will be able to identify key features of time series, uplift, and logistic models.
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Predictive Analytics: Features of Predictive Analytics Models
After watching this video, you will be able to identify key features of predictive analytics.
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Predictive Analytics: Big Data
After watching this video, you will be able to recognize key features of big data.
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Predictive Analytics: Predictive Analytics vs. Traditional BI
After watching this video, you will be able to recognize key differences between predictive analytics and traditional business intelligence.
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Predictive Analytics: Sales, Marketing, and Operations
After watching this video, you will be able to illustrate a marketing or sales application of predictive analytics.
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Predictive Analytics: Data Warehousing and Data Marts
After watching this video, you will be able to recognize the important features of data warehousing and marts.
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Predictive Analytics: Relational Database Management System and Hadoop
After watching this video, you will be able to identify key features of relational database management system (RDBMS) and Hadoop.
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Predictive Analytics: Common Data Sources
After watching this video, you will be able to identify common sources of data.
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Predictive Analytics: Extract, Transform, and Load Data
After watching this video, you will be able to recognize key concepts of extracting, transforming, and loading data.
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Predictive Analytics: Data Collection Considerations
After watching this video, you will be able to identify important aspects of data collection.
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Predictive Analytics: Data Collection Strategy
After watching this video, you will be able to recognize elements of data collection strategy.
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Predictive Analytics: Data Exploration Objectives
After watching this video, you will be able to recognize various ways exploration helps in understanding data.
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Predictive Analytics: Prescriptive Data Analytics
After watching this video, you will be able to recognize key features of prescriptive analytics.
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Predictive Analytics: What Is Data Mining?
After watching this video, you will be able to recognize key features of data mining.
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Predictive Analytics: Data Exploration Roadmap
After watching this video, you will be able to list key steps in the data exploration roadmap.
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Predictive Analytics: Descriptive Data Analytics
After watching this video, you will be able to recognize key features of descriptive analytics.
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Predictive Analytics: Correlation and Predictive Analytics
After watching this video, you will be able to recognize how correlation is used in predictive analytics.
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Predictive Analytics: Correlation and Causation
After watching this video, you will be able to recognize when correlation indicates causation and when it doesn't.
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Predictive Analytics: Multivariate Analysis: Testing Goodness-of-Fit
After watching this video, you will be able to determine if a data sample is representative of the data population.
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Predictive Analytics: Overview of Correlation
After watching this video, you will be able to identify key features of correlation.
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Predictive Analytics: Statistical Significance of Correlation
After watching this video, you will be able to distinguish between statistical versus practical significance.
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Predictive Analytics: Introduction to Regression Analysis
After watching this video, you will be able to recognize the role of regression in predictive analytics.
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Predictive Analytics: Best Fit and Residual Analysis
After watching this video, you will be able to identify how the predictive power of a model can be assessed using the r-squared metric.
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Predictive Analytics: Choosing Predictive Data
After watching this video, you will be able to identify what data is valuable for prediction.
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Predictive Analytics: Timing and Quantity of Data
After watching this video, you will be able to recognize the different data time frames and quantity of data needed to build predictive models.
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Predictive Analytics: Logistic Regression for Predictive Analytics
After watching this video, you will be able to recognize key features of logistic regression.
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Predictive Analytics: Identify the Regression Technique
After watching this video, you will be able to identify the correct regression technique to use in a given situation.
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Predictive Analytics: Data Measurement Scales
After watching this video, you will be able to recognize features of data measurement scales.
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Predictive Analytics: Descriptive vs. Inferential Statistics
After watching this video, you will be able to recognize features of descriptive and inferential statistics.
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Predictive Analytics: Predictive Analytics and Statistics
After watching this video, you will be able to recognize the role of statistics in predictive analytics.
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Predictive Analytics: Types of Data
After watching this video, you will be able to recognize attributes of qualitative, quantitative, discrete, and continuous data.
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Predictive Analytics: Conditional Probability and Bayes Rule
After watching this video, you will be able to apply Bayes theorem in a given situation.
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Predictive Analytics: Probability Overview and Probabilistic Events
After watching this video, you will be able to recognize basic features of probability and the types of probabilistic events.
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Predictive Analytics: Addition and Multiplication Rules
After watching this video, you will be able to apply addition and multiplication rules for a probabilistic event.
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Predictive Analytics: Univariate Analysis: CI for Hypothesis Testing
After watching this video, you will be able to recognize how confidence intervals (CI) are used for hypothesis testing.
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Predictive Analytics: Multivariate Analysis: Testing for Differences
After watching this video, you will be able to recognize key features of testing for differences in mean and testing for differences in proportion.
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Predictive Analytics: Permutations and Combinations
After watching this video, you will be able to distinguish between permutations and combinations.
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Predictive Analytics: Univariate Analysis: Minimizing the Margin of Error
After watching this video, you will be able to recognize how to reduce the margin of error.
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Predictive Analytics: Government and Crime Prevention
After watching this video, you will be able to illustrate a government or academia application of predictive analytics.
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Predictive Analytics: The Predictive Analytics Project
After watching this video, you will be able to list features of a predictive analytics project.
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Predictive Analytics: Banking and Insurance
After watching this video, you will be able to illustrate a banking or insurance application of predictive analytics.
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Predictive Analytics: Technology and Healthcare
After watching this video, you will be able to illustrate a technology or healthcare application of predictive analytics.
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Predictive Analytics: Collecting and Preparing Data
After watching this video, you will be able to recognize important considerations for preparing data to build a model.
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Predictive Analytics: Building and Training a Predictive Model
After watching this video, you will be able to outline the process of building and training a predictive model.
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Predictive Analytics: Identifying Project Stakeholders and Roles
After watching this video, you will be able to identify project stakeholders and roles.
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Predictive Analytics: Project Requirements and Considerations
After watching this video, you will be able to identify predictive analytics and project considerations.
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Predictive Analytics: Monitoring Model Usefulness and Applying Knowledge
After watching this video, you will be able to recognize important considerations for model usefulness and key features of knowledge application.
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Predictive Analytics: Identify the Type of Analytics
After watching this video, you will be able to recognize the type of analytics presented in examples.
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Predictive Analytics: Predictive Analytics Implementation
After watching this video, you will be able to identify key considerations and tools for predictive analytics implementation.
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Predictive Analytics: Distance and Weight Measures for Numeric Attributes
After watching this video, you will be able to recognize distance and weighted distance measures.
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Predictive Analytics: Proximity Measures for Non-numeric Attributes
After watching this video, you will be able to recognize proximity measures for non-numeric attributes.
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Predictive Analytics: Overview of the k-NN Algorithm
After watching this video, you will be able to recognize features of the k-NN algorithm.
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Predictive Analytics: Basic Artificial Neural Networks
After watching this video, you will be able to recognize steps and considerations to building artificial neural networks.
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Predictive Analytics: Advanced Artificial Neural Network Concepts
After watching this video, you will be able to recognize the purpose of nonlinear activation functions and methods to find the global minimum SSE.
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Predictive Analytics: Implementing the k-NN Algorithm
After watching this video, you will be able to implement the k-NN algorithm.
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Predictive Analytics: Overview of Artificial Neural Networks
After watching this video, you will be able to identify key features of artificial neural networks.
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Predictive Analytics: Important Parameters for Artificial Neural Networks
After watching this video, you will be able to recognize important parameters for artificial neural networks.
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Predictive Analytics: Implementing an Artificial Neural Network
After watching this video, you will be able to implement an artificial neural network.
