How Walmart uses data science
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Data Science Full Course – Learn Data Science in 10 Hours | Data Science For Beginners | Edureka
EDUREKA!
Undoubtedly, Data Science is one of the most revolutionary technologies of our era. It involves deriving useful insights from data to solve complex real-world problems. This session is a full course on Data Science that covers everything you need to know to master the field.
Before we get started, let’s take a look at the agenda. The first module is an introduction to Data Science, which covers all the basic fundamentals. Next, we have the Statistics and Probability module, where you’ll understand the math behind Data Science and Machine Learning algorithms. Then, we have the Basics of Machine Learning module, where you’ll learn about different types of Machine Learning algorithms.
After that, we move on to the Supervised Learning Algorithms module, which covers Linear Regression, Logistic Regression, Decision Trees, Random Forest, K-Nearest Neighbor, and Naive Bias. Each of these modules explores how these algorithms can be used to solve complex problems with the help of real-world examples.
Introduction to Data Science
Data science is currently one of the most in-demand technologies due to the increasing amount of data being generated and the need to process and make sense of it. In this session, we will discuss data science in depth, including its various sources, the data life cycle, machine learning, and more.
AGENDA
Sources of data
How Walmart uses data science
What is data science?
Who are data scientists?
Data science job roles
Data life cycle
Basics of machine learning
K-means algorithm and use case
SOURCES OF DATA
The evolution of technology and the introduction of IoT and social media have led to an explosion of data being generated. Sources of data include:
Weblogs and web traffic
Sensor data
Mobile devices
Social media
Cloud applications
HOW WALMART USES DATA SCIENCE
Walmart uses data science to gain insights from their database, such as identifying patterns in customer behavior to increase sales potential.
WHAT IS DATA SCIENCE?
Data science involves using statistical and computational methods to extract insights and knowledge from data. It includes data analysis, machine learning, and artificial intelligence.
WHO ARE DATA SCIENTISTS?
Data scientists have a strong background in mathematics and statistics, as well as programming skills. They have expertise in data mining, data analysis, and machine learning.
DATA SCIENCE JOB ROLES
Job roles in data science include:
Data analyst
Data architect
Data engineer
Machine learning engineer
Business intelligence analyst
DATA LIFE CYCLE
The data life cycle involves:
Data extraction
Data processing
Data analysis
Data visualization
Data storage
Data security
BASICS OF MACHINE LEARNING
Machine learning involves using algorithms to automatically learn patterns in data and make predictions or decisions without being explicitly programmed. Types of machine learning include supervised, unsupervised, and reinforcement learning.
K-MEANS ALGORITHM AND USE CASE
The K-means algorithm is a clustering algorithm used to group data points together based on their similarity. A use case could be clustering movies based on their popularity on social media platforms.
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