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BADIR: Hands-on Predictive Analytics
Section 0
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Monthly mentoring session - Zoom link and calendar invite
Section 1 - New recording
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BADIR step 1: Business Question (20:13)
BADIR step 2: Analysis Plan (43:17)
BADIR step 2: Analysis Plan Results (32:32)
R programming
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Getting started with R (8:01)
R: Introduction (20:40)
R: Exploring Data (39:24)
R: Indexing and apply family of functions (44:00)
R: Correlation (19:51)
R Programming
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R: Exercise review (18:56)
R: Vectors (50:49)
R: Outliers treatment and plotting (44:59)
R Programming
Downloads and link to join
R: Data Preparation using DPLYR (41:46)
R: Missing Value Treatment (34:03)
R: Variable Reduction (29:43)
Mentoring Session
Post your questions here
Section 1
Section1 Downloads
BADIR step 1: Business Question (13:08)
BADIR step 2: Analysis Plan
BADIR step 3: Data Collection (27:25)
Section 2
Section 2 Downloads
BADIR step 4: Insights (13:37)
BADIR step 4: Insights - Data Preparation - Missing values (43:07)
BADIR step 4: Insights - Data Preparation - Outliers and low information variables (25:21)
BADIR step 4: Insights/Build Model - Variable Reduction (35:39)
BADIR: Insights using Knime (19:54)
Section 3
Section 3 Downloads
BADIR step 4: Insights/Build Model - Variable Transformation (12:36)
BADIR step 4: Insights/Build Model - Variable Transformation Example (30:42)
BADIR step 4: Insights/Build Model - Model Building [Regression]- part 1 (14:44)
BADIR step 4: Insights/Build Model - Model Building [Regression]- part 2 (25:45)
BADIR step 4: Insights/Build Model - Model Building [Regression]- part 3 (32:24)
Section 4
Section 4 Downloads
Exercise Review (14:04)
Decision Tree (10:25)
BADIR step 4: Insights/Build Model - Model Building [Decision Tree] (38:32)
BADIR step 4: Insights/Build Model - Model Validation/Comparison (22:13)
Section 5
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BADIR - Recap (11:33)
BADIR step 4: Insights/Findings - Quantify Impact - 1 (16:57)
BADIR step 4: Insights/Findings - Quantify Impact - 2 (41:35)
BADIR step 5: Recommendations (29:18)
Section 6
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BADIR - Predictive Analytics recap (21:05)
Introduction to case (3:23)
CASE SIMULATION - Business Question (13:43)
CASE SIMULATION - Analysis Plan (20:21)
CASE SIMULATION: Insights- Data Preparation (14:02)
Section 7
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CASE SIMULATION: Insights- Data Preparation (25:39)
CASE SIMULATION - case (10:48)
CASE SIMULATION: Insights- Variable transformation (19:10)
CASE SIMULATION: Insights - Build Models (34:04)
CASE SIMULATION: Insights - Model validation (19:18)
Section 8
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CASE SIMULATION - Quantifying impact -1 (5:13)
CASE SIMULATION - Quantifying impact -2 (16:57)
CASE SIMULATION - Recommendation -1 (12:57)
CASE SIMULATION - Recommendation -2 (15:15)
K-means clustering (29:34)
Section 9
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BADIR: K- means clustering (42:19)
Customer Segmentation using K-Means Clustering - 1 (43:58)
Customer Segmentation using K-Means Clustering -2 (33:20)
Section 10
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Introduction to Text Analytics (13:40)
BADIR: Text Analytics (19:31)
Text Analytics using Python (86:06)
Recommendations (6:55)
Section 11
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Python - Fundamentals (45:50)
Neural Networks (39:52)
Building Model with Python (30:39)
Section 12
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Demystifying Space - Machine Learning, AI, Deep Learning, Neural Networks
AI (20:53)
Building a neural network model (36:07)
Pitfalls and closer (25:36)
Course completion certificate and survey
Certificate and Survey
Section1 Downloads
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