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Videos
About
25:23
13-2 Analyzing Health Text Data - Why Common Words Are Not Useful and How tf-idf Can Help
27:22
13-1 Analyzing Health Text Data - Reading in Text Data and Calculating Term Frequencies
21:18
11-5 Supervised Learning Algorithms - Combining Classifiers
8:34
11-4 Supervised Learning Algorithms - Review of Supervised Learning Algorithms
28:35
11-3 Supervised Learning Algorithms - Naive Bayes
14:34
11-2 Supervised Learning Algorithms - Perceptrons and Neural Networks
22:17
11-1 Supervised Learning Algorithms - Support Vector Machines
18:32
10-4 Machine Learning and Missing Data - Diagnosing Missing Values
7:48
10-3 Machine Learning and Missing Data - Why Are the Data Missing?
5:01
10-2 Machine Learning and Missing Data - The Missing Data Problem In a Nutshell
14:56
10-1 Machine Learning and Missing Data - Review of Key ML Concepts and Performance Measures
10:33
9-5 Supervised Learning Algorithms - Lazy Learners
34:58
9-4 Supervised Learning Algorithms - Decision Trees
16:28
9-3 Supervised Learning Algorithms - Evaluation Measures
7:53
9-2 Supervised Learning Algorithms - The Majority Baseline
20:23
9-1 Supervised Learning Algorithms - What is Supervised Learning?
20:26
7-6 Interactive Data Analysis - Live Coding - Converting an Rmd Document to an Interactive Document
35:44
7-5 Interactive Data Analysis - Converting R Markdown Documents into Interactive Shiny Documents
11:04
7-4 Interactive Data Analysis - Live Coding - Converting an R Notebook into an R Markdown Document
25:50
7-3 Interactive Data Analysis - Converting R Notebooks into R Markdown Documents
29:19
8-6 Introduction to ML - Step-by-Step Process for Training and Evaluating Models Using Tidymodels
24:48
8-5 Introduction to ML - Common Problems with Fitting and Applying Models
23:17
8-4 Introduction to ML - Supervised Learning is a Curve-Fitting Exercise
15:11
8-3 Introduction to ML - Is a Predictive Model Needed and Should You Develop One?
9:04
8-2 Introduction to ML - Reinforcement Learning and ML vs Stats Terminology
12:44
8-1 Introduction to ML - Unsupervised and Supervised Learning
9:17
7-2 Interactive Data Analysis - R Tips of the Day - The magic of !!parse_expr()
3:44
7-1 Interactive Data Analysis - Overview of Content
5:43
6-8 Hypothesis Testing - Key Lessons
30:42
6-6 Hypothesis Testing - Which Test, Which Plot
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