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DP-100: Designing and Implementing a Data Science Solution on Azure

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Duration

09:42:32 h

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$14.99

Curriculum for DP-100 Certification Video Course

Basics of Machine Learning

6 Lectures

Time 00:46:51

Getting Started with Azure ML

6 Lectures

Time 00:26:48

Data Processing

6 Lectures

Time 01:09:56

Classification

15 Lectures

Time 02:14:36

Hyperparameter Tuning

1 Lectures

Time 00:09:53

Deploy Webservice

3 Lectures

Time 00:12:28

Regression Analysis

10 Lectures

Time 01:01:07

Clustering

3 Lectures

Time 00:33:11

Data Processing - Solving Data Processing Challenges

15 Lectures

Time 01:19:50

Feature Selection - Select a subset of Variables or features with highest impact

9 Lectures

Time 00:45:33

Recommendation System

6 Lectures

Time 01:02:19

Name of Video	Time
1. What You Will Learn in This Section	02:02
2. Why Machine Learning is the Future?	10:30
3. What is Machine Learning?	09:31
4. Understanding various aspects of data - Type, Variables, Category	07:06
5. Common Machine Learning Terms - Probability, Mean, Mode, Median, Range	07:41
6. Types of Machine Learning Models - Classification, Regression, Clustering etc	10:02

Name of Video	Time
1. What You Will Learn in This Section?	02:08
2. What is Azure ML and high level architecture.	03:59
3. Creating a Free Azure ML Account	02:21
4. Azure ML Studio Overview and walk-through	05:01
5. Azure ML Experiment Workflow	07:20
6. Azure ML Cheat Sheet for Model Selection	06:01

Name of Video	Time
1. Data Input-Output - Upload Data	08:18
2. Data Input-Output - Convert and Unpack	08:53
3. Data Input-Output - Import Data	05:46
4. Data Transform - Add Rows/Columns, Remove Duplicates, Select Columns	11:34
5. Data Transform - Apply SQL Transformation, Clean Missing Data, Edit Metadata	18:29
6. Sample and Split Data - How to Partition or Sample, Train and Test Data	16:56

Name of Video	Time
1. Logistic Regression - What is Logistic Regression?	06:46
2. Logistic Regression - Build Two-Class Loan Approval Prediction Model	22:09
3. Logistic Regression - Understand Parameters and Their Impact	11:19
4. Understanding the Confusion Matrix, AUC, Accuracy, Precision, Recall and F1Score	13:17
5. Logistic Regression - Model Selection and Impact Analysis	05:50
6. Logistic Regression - Build Multi-Class Wine Quality Prediction Model	08:13
7. Decision Tree - What is Decision Tree?	07:35
8. Decision Tree - Ensemble Learning - Bagging and Boosting	07:05
9. Decision Tree - Parameters - Two Class Boosted Decision Tree	05:34
10. Two-Class Boosted Decision Tree - Build Bank Telemarketing Prediction	10:43
11. Decision Forest - Parameters Explained	03:37
12. Two Class Decision Forest - Adult Census Income Prediction	14:43
13. Decision Tree - Multi Class Decision Forest IRIS Data	08:14
14. SVM - What is Support Vector Machine?	04:02
15. SVM - Adult Census Income Prediction	05:32

Name of Video	Time
1. Tune Hyperparameter for Best Parameter Selection	09:53

Name of Video	Time
1. Azure ML Webservice - Prepare the experiment for webservice	02:22
2. Deploy Machine Learning Model As a Web Service	03:28
3. Use the Web Service - Example of Excel	06:38

Name of Video	Time
1. What is Linear Regression?	06:19
2. Regression Analysis - Common Metrics	06:27
3. Linear Regression model using OLS	10:54
4. Linear Regression - R Squared	04:26
5. Gradient Descent	10:48
6. Linear Regression: Online Gradient Descent	02:12
7. LR - Experiment Online Gradient	04:21
8. Decision Tree - What is Regression Tree?	06:41
9. Decision Tree - What is Boosted Decision Tree Regression?	02:00
10. Decision Tree - Experiment Boosted Decision Tree	07:01

Name of Video	Time
1. What is Cluster Analysis?	11:52
2. Cluster Analysis Experiment 1	13:16
3. Cluster Analysis Experiment 2 - Score and Evaluate	08:04

Name of Video	Time
1. Section Introduction	02:49
2. How to Summarize Data?	06:29
3. Summarize Data - Experiment	03:12
4. Outliers Treatment - Clip Values	06:52
5. Outliers Treatment - Clip Values Experiment	07:51
6. Clean Missing Data with MICE	07:19
7. Clean Missing Data with MICE - Experiment	06:44
8. SMOTE - Create New Synthetic Observations	08:33
9. SMOTE - Experiment	05:50
10. Data Normalization - Scale and Reduce	03:11
11. Data Normalization - Experiment	02:32
12. PCA - What is PCA and Curse of Dimensionality?	06:24
13. PCA - Experiment	03:24
14. Join Data - Join Multiple Datasets based on common keys	06:03
15. Join Data - Experiment	02:43

Name of Video	Time
1. Feature Selection - Section Introduction	05:48
2. Pearson Correlation Coefficient	04:36
3. Chi Square Test of Independence	05:34
4. Kendall Correlation Coefficient	04:11
5. Spearman's Rank Correlation	03:42
6. Comparison Experiment for Correlation Coefficients	07:40
7. Filter Based Selection - AzureML Experiment	03:33
8. Fisher Based LDA - Intuition	04:43
9. Fisher Based LDA - Experiment	05:46

Name of Video	Time
1. What is a Recommendation System?	16:57
2. Data Preparation using Recommender Split	08:34
3. What is Matchbox Recommender and Train Matchbox Recommender	08:33
4. How to Score the Matchbox Recommender?	05:43
5. Restaurant Recommendation Experiment	13:36
6. Understanding the Matchbox Recommendation Results	08:58

Microsoft Data Science DP-100 Exam Dumps, Practice Test Questions

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DP-100 Premium Bundle

Premium File: 517 Questions & Answers. Last update: Dec 3, 2024
Training Course: 80 Video Lectures
Study Guide: 608 Pages

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DP-100 Premium Bundle

Premium File: 517 Questions & Answers. Last update: Dec 3, 2024
Training Course: 80 Video Lectures
Study Guide: 608 Pages

Latest Questions
100% Accurate Answers
Fast Exam Updates

$69.97

$49.99

Free DP-100 Exam Questions & DP-100 Dumps

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Microsoft DP-100 Training Course

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