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A dive into the Data Analytics journey: Data Processing & Analysis (3/3)

Microsoft Reactor
113K subscribers
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252 views Streamed 2 years ago
In this series of sessions, Hadeel will take you on a journey in Data Analytics, where she will be exploring each stage separately. In the first phase, we walked through the steps and aspects to consider to clean your data and get it prepared to be processed and used to extract insights and make decisions (Data cleaning & preprocessing). We then applied Exploratory data analysis to investigate our dataset and summarize main characteristics and highlight significant factors. Then, we applied data visualization techniques to identify patterns and trends in our dataset using visual methods – such as graphs, charts and plots. The next step is data processing & model deployment. In data processing, we will focus on model selection, building, and testing. Prediction models is also used in this step. After deploying our model to the dataset, the last and final step in the data analytics lifecycle is data analysis. After going through all the phases, we …...more
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Speaker

3:30

Data Science Life Cycle

4:10

What Is Data Science

4:40

The Data Science Life Cycle

5:17

The Data Science Process

5:29

Processing Your Data

5:38

Data Processing

6:24

Data Processing and Analytics

9:00

What Is Data Processing

9:47

Why Do We Manipulate Data

9:57

Where Data Processing Is Used

11:25

Data Analysis

12:16

What Data Analytics Is

13:13

Select the Right Model for Your Data Set

13:55

Types of Data Analytics

14:45

What Are the Types of Data Analytics

15:19

Descriptive Analytics

15:54

Diagnostic Analysis

17:16

Predictive Analysis

18:03

Business Applications of Predictive Analysis

18:52

Prescriptive Analysis

19:24

Analytics Types of Analytics

20:09

Quest Considerations

21:20

Build the Model

22:01

Deploy the Model

22:36

Machine Learning Algorithms

24:13

Supervised Learning

25:03

Reinforcement Learning

25:39

Types of Algorithms for Supervised Learning

27:24

Classification Algorithms

29:49

Logistic Regression

29:55

Naive Bayes

30:56

Decision Trees

31:59

Popular Regression Algorithms

32:50

Linear Regression

33:14

Linear Regression Function Graph

33:41

Multilinear Regression

34:43

Multi Linear Regression

35:18

Distribution of Charges

41:43

Plot the Correlation between the Age and the Cost of Treatment

44:12

Plot the Correlation between the Bmi and the Cost of Treatment

45:20

The Impact of Bmi on the Cost of Treatment

46:34

The Data Preprocessing

47:52

Removing Unused Columns

48:51

Convert Categorical or Non-Numerical Columns to Numerical

49:33

Normalize Our Data Using the Minimum Maximum Normalization

50:25

Analyzing Data Using the Python Library

58:04

Microsoft Learn

58:26
A dive into the Data Analytics journey: Data Processing & Analysis (3/3)
In this series of sessions, Hadeel will take you on a journey in Data Analytics, where she will be exploring each stage separately. In the first phase, we walked through the steps and aspects to consider to clean your data and get it prepared to be processed and used to extract insights and make decisions (Data cleaning & preprocessing). We then applied Exploratory data analysis to investigate our dataset and summarize main characteristics and highlight significant factors. Then, we applied data visualization techniques to identify patterns and trends in our dataset using visual methods – such as graphs, charts and plots. The next step is data processing & model deployment. In data processing, we will focus on model selection, building, and testing. Prediction models is also used in this step. After deploying our model to the dataset, the last and final step in the data analytics lifecycle is data analysis. After going through all the phases, we will analyze our data and interpret the results. This part is essential because it’s how a business will gain actual value from the previous steps. What will you learn? As we explore and dig deeper into the Data Analytics process, you will learn how to process and analyze your data. We will go through the data processing & analysis steps in details, helping you gain an understanding of what the process looks like. Who is it aimed at? Beginners to Python and Data Science. Some familiarity with programming recommended. Anyone interested in diving deep into the Data Science field. More learning/prerequisites: For further learning, the following learn module is recommended, available on Microsoft Learn: https://aka.ms/DeepDiveDataAnalytics_LM Speaker: Hadeel Shubair Speaker Bio: Hadeel is a Regional Cloud Advocate and Data Analytics Engineer for Microsoft, Middle East/Africa region. She holds a Master’s degree in Data Analytics and is passionate about learning and sharing her knowledge on tech topics including Data Analytics, AI, & ML. Before joining Microsoft, Hadeel held several appointments and roles including Google Women in Tech scholar through which she delivered several sessions to the community to motivate and empower young talents. Hadeel also served as part of the Data & Communications team overlooking the organization of the World Government Summit. On the other side, while at University, Hadeel chaired the Women in Engineering club, and was the Chief Editor of the Engineering Newsletter. As a Cloud Advocate for the Microsoft Reactor, Hadeel’s main goal is to take you on a journey to understand & learn more about Data and AI concepts and applications. She's passionate about technology, education, & growing the Data & AI community across the region. [eventID:16751]

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Microsoft Reactor

113K subscribers
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