ML with PySpark: Customer Churn Analysis
Develop a machine learning model using PySpark to forecast customer attrition and acquire practical experience in AI-driven business solutions.
Description for ML with PySpark: Customer Churn Analysis
Solution for Business Issues Driven by AI: Utilize artificial intelligence (AI) to develop machine learning models that are designed to address real-world business challenges, such as the prediction of consumer churn.
Developing a Machine Learning Model with PySpark: Acquire practical experience with PySpark to efficiently construct, train, and assess machine learning models.
PySpark Data Cleansing: Master the application of fundamental data purification techniques to guarantee the production of high-quality data that is suitable for the development of precise models.
Customer Churn Prediction: Concentrate on identifying the factors that contribute to consumer churn, thereby offering businesses actionable insights to enhance retention.
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Coursera Project Network
Duration: 2 hours at your own pace
Schedule: Hands-on learning
Pricing for ML with PySpark: Customer Churn Analysis
Use Cases for ML with PySpark: Customer Churn Analysis
FAQs for ML with PySpark: Customer Churn Analysis
Reviews for ML with PySpark: Customer Churn Analysis
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for ML with PySpark: Customer Churn Analysis
Featured Tools
The specialization caters to machine learning professionals seeking TensorFlow skills through a structured progression from basics to advanced topics, emphasizing practical application through capstone projects.
This course explores enterprise machine learning applications, assesses the viability of ML use cases, and addresses the prerequisites, data characteristics, and critical factors for developing and managing ML models.
Learn to use the latest LLM APIs, the LangChain Expression Language (LCEL), and develop a conversational agent.
Introduces the fundamental procedures for the development, scripting, and training of a machine-learned model in Google Cloud.
This program involves the principles of Python, data analysis, workflow automation, and machine learning applications.
Compare & Review AI Tool Directory AI Course Marketplace
AI Tool Categories
AI Productivity ToolsAI Image GeneratorsAI Text GeneratorsAI Video GeneratorsAI Audio GeneratorsAI Art GeneratorsMisc AI ToolsAI Code GeneratorsFree AI ToolsAI Functions
Marketing AI ToolsAI Tools for EducationAI Tools for ResearchAI Tools for FinanceAI Project Management ToolsLegal AI ToolsAI Tools for E-commerceAI Agents For AutomationAI Tools for BusinessAI Tools for Real EstateAI Course Categories
AI & Machine Learning CoursesGenerative AI CoursesData Science CoursesComputer Science CoursesAI Courses for BeginnersContact Us: info@groupify.ai
Aimed Labs