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What you'll learn?
- In this course you will implement Spark Machine Learning Project Telecom Customer Churn Prediction in Apache Spark using Databricks Notebook (Community edition server)
- Launching Apache Spark Cluster
- Process that data using a Machine Learning model (Spark ML Library)
Course Overview
Spark Machine Learning Project (Telecom Customer Churn Prediction) for beginners using Databricks Notebook (Unofficial) (Community edition Server)
In this Data science Machine Learning project, we will create Telecom Customer Churn Prediction Project using Classification Model Logistic Regression, Naive Bayes and One-vs-Rest classifier few of the predictive models.
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Explore Apache Spark and Machine Learning on the Databricks platform.
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Launching Spark Cluster
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Process that data using a Machine Learning model (Spark ML Library)
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Hands-on learning
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Real time Use Case
Telecom Customer Churn Prediction a Real time Use Case on Apache Spark
About Databricks:
Databricks lets you start writing Spark ML code instantly so you can focus on your data problems.
Pre-requisites
- Apache Spark basic and Scala fundamental knowledge is required and SQL Basics
- Following browsers on Windows, Linux or macOS desktop:
- Google Chrome (Latest version), Firefox (Latest version), Safari (Latest version), Microsoft Edge* (Latest version)
- Internet Explorer 11* on Windows 7, 8, or 10 (with latest Windows updates applied)
- *You might see performance degradation for some features on Microsoft Edge and Internet Explorer.
- The following browsers are not supported:
- Mobile browsers.
- Beta, “preview,” or otherwise pre-release versions of desktop browsers.
Target Audience
- Beginner Apache Spark Developer, Bigdata Engineers or Developers, Software Developer, Machine Learning Engineer, Data Scientist
Curriculum 14 Lectures 01:43:19
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Section 1 : Customer Churn Prediction in Apache Spark
- Lecture 2 :
- Download Resources
- Lecture 3 :
- Introduction to Spark
- Lecture 4 :
- Free Account creation in Databricks
- Lecture 5 :
- Provisioning a Spark Cluster
- Lecture 6 :
- Introduction to Machine Learning
- Lecture 7 :
- Basics about Notebook
- Lecture 8 :
- Dataframes
- Lecture 9 :
- Project Explaination Part1
- Lecture 10 :
- Project Explaination Part2
- Lecture 11 :
- Project Explaination Part3
- Lecture 12 :
- Project Explaination Part5
- Lecture 13 :
- Important Lecture
- Lecture 14 :
- Project Explaination Part4
Our learners work at
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Instructor
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I am Solution Architect with 12+ year’s of experience in Banking, Telecommunication and Financial Services industry across a diverse range of roles in Credit Card, Payments, Data Warehouse and Data Center programmes
My role as Bigdata and Cloud Architect to work as part of Bigdata team to provide Software Solution.
Responsibilities includes,
- Support all Hadoop related issues
- Benchmark existing systems, Analyse existing system challenges/bottlenecks and Propose right solutions to eliminate them based on various Big Data technologies
- Analyse and Define pros and cons of various technologies and platforms
- Define use cases, solutions and recommendations
- Define Big Data strategy
- Perform detailed analysis of business problems and technical environments
- Define pragmatic Big Data solution based on customer requirements analysis
- Define pragmatic Big Data Cluster recommendations
- Educate customers on various Big Data technologies to help them understand pros and cons of Big Data
- Data Governance
- Build Tools to improve developer productivity and implement standard practices
I am sure the knowledge in these courses can give you extra power to win in life.
All the best!!
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