Customer Segmentation Tutorial | Python Projects | K-Means Algorithm | Python Training | Edureka

🔥Machine Learning Engineer Masters Program:https://www.edureka.co/masters-program/machine-learning-engineer-training
This Edureka video on "Customer Segmentation” will provide you with comprehensive and detailed knowledge of Machine Learning concepts with a hands-on project where you will learn how to segment customer data using appropriate algorithms in Python. Following pointers are covered in this Customer Segmentation video:
00:00:00 Introduction
00:01:15 About the Project
00:04:19 What is Customer Segmentation?
00:04:53 Types of Segmentation Factors
00:08:14 Advantages Of Customer Segmentation
00:11:05 Why Machine Learning?
00:12:16 Unsupervised Learning
00:14:02 K-Means Algorithm
00:18:49 Environments and Tools For Project
00:20:46 Demo

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About the Masters Program
Edureka’s Machine Learning Engineer Masters Program makes you proficient in techniques like Supervised Learning, Unsupervised Learning and Natural Language Processing. It includes training on the latest advancements and technical approaches in Artificial Intelligence & Machine Learning such as Deep Learning, Graphical Models and Reinforcement Learning. The Master's Program covers the following topics:

🔹Python Programming Certification Course - http://bit.ly/39g0R9u
🔸Machine Learning Certification Training using Python - http://bit.ly/2MPmCW1
🔹Graphical Models Certification Training - http://bit.ly/3nAuKpY
🔸Reinforcement Learning - http://bit.ly/2K4FG1F
🔹Natural Language Processing with Python Certification Course - http://bit.ly/2LAAcMq
🔸Deep Learning with TensorFlow 2.0 Certification Training - http://bit.ly/2XtbKzp
🔹Python Spark Certification Training using PySpark - http://bit.ly/39ljmcD

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Prerequisites

There are no prerequisites for enrollment to the Masters Program. However, as a goodwill gesture, Edureka offers a complimentary self-paced course in your LMS on SQL Essentials to brush up on your SQL Skills. This program is designed and developed for an aspirant planning to build a career in Machine Learning or an experienced professional working in the IT industry.

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