05:12
ANN Summary
10:13
Boosted Trees for Regression
05:55
The Derivation of a ROC Curve with an Example
21:23
ROC Charts and Decile Charts
30:10
Measures of Classification Model Quality
16:12
Ch9 HW Solution Walk Through
23:21
Lecture 10. Time series forecasting with Multiple Linear Regression
05:45
5 Example MLR problem in JMP
04:20
Create Correlation Matrix in Excel
18:10
9 Related input variables
08:55
1 What does it mean to have a hardened heart
09:47
Building and Evaluation Decision Tree Models In SAS JMP
06:32
How to evaluate ScikitLearn classification model results
07:46
The Basics of Formatting Strings and Numbers in Python 3
01:18
Launch Jupyter Notebook in Mac Folder or your choice
07:49
4 ROC Curves
11:59
3 Boosted Trees, Random Forests, SVM
08:49
2 KNN and ANN
13:55
1 Summary comparison of predictive algorithms
10:12
How Neural Networks work
08:28
Prepare data and test for overfitting in KNN with all input variables
02:46
Starting Jupyter Notebook in the MS Windows folder of your choice
03:28
Data types and Partition data in JMP
03:42
Generate Correlation Matrix in JMP and Evaluate Collinearity
06:45
Performing Multiple Linear Regression (MLR) in JMP
10:10
Python 2 Part 4: The Logistic Regression and Decision Tree Model
15:36
Python 2 Part 2: Data Prep and Feature Engineering
10:28
Python 2 Part 3: Producing and evaluating first model
10:25
Python 2 Part 1: Data Intro and Visualizations
05:28
Data visualization and charts with matplotlib
10:07
Exploratory data analysis EDA in pandas
12:54
DataFrames in pandas for data science with Python
07:36
series in pandas
03:07
Launch Jupyter Notebook in Mac in the Directory of your choice
07:20
Command Mode and Keyboard Shortcuts in Jupyter Notebook
01:47
Starting in Jupyter Notebook in MS Windows in the Folder of your Choice
03:07
How to Create a Shell script to launch Jupyter Notebook in Mac OS X
03:14
5 How to Insert Videos into MyEducator
06:21
4 How to Insert Images in MyEducator
03:10
3 Editing through the MyEducator Interface
03:35
2 Using VS Code and Basic Structure of DocBook XML
02:35
1 Download and Upload MyEducator DocBooks
06:34
Create Azure Web Service for use with Excel
04:54
Converting text to numbers in excel and JMP
06:02
Collinearity and distorted regression Coefficients
06:10
Training, Validation, and Test Partitions
04:51
Correlation matrix and Collinearity
09:56
Comparing models using a template
06:45
Preliminary Evaluation
08:17
Deriving Time Series Data from Dates in JMP
04:26
Regression based time series forecasting Part 2
07:21
Regression based time series forecasting Part 1
04:10
Create time series data from Years and Quarters in JMP
03:15
Deriving the Sequential Time Index for Months in JMP
07:20
Intperpreting Binary Decision Trees in Azure ML Studio
04:21
multivariate outlier detection in JMP
11:31
Getting started with Azure and an example experiment
07:39
Data Prep for Forecasting From Integers
04:33
Creating a Balanced Sample in VisMiner
10:25
Using VisMiner for file operations, If statements, and using PP to select subpopulations
X
About
Tags