Life Expectancy Prediction Using ML
The course outlines steps to understand linear regression theory, conduct exploratory data analysis, and create, train, and assess a linear regression model.
Description for Life Expectancy Prediction Using ML
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Coursera Project Network
Duration: 1.5 hours
Schedule: Flexible
Pricing for Life Expectancy Prediction Using ML
Use Cases for Life Expectancy Prediction Using ML
FAQs for Life Expectancy Prediction Using ML
Reviews for Life Expectancy Prediction Using ML
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Life Expectancy Prediction Using ML
Relationchips is an AI data agent that automates dashboards and actions, incorporates tools, and queries data in natural language, all without the need for SQL.
Chat2Report facilitates the conversational AI-driven analysis of over a decade of SEC financial reports for US-listed companies.
EquityResearch.ai offers AI-driven stock analysis and business insights, facilitating investment evaluation through impartial, data-centric reports.
NeoBase is an AI-powered assistant that facilitates natural language interaction, optimization, and administration across multiple databases with complete self-hosting capabilities.
From fundamental concepts to advanced methods such as deep learning and ensemble techniques, this program provides a comprehensive examination of machine learning techniques.
Acquire practical expertise in the integration of machine learning models into pipelines, optimizing performance, and efficiently managing versioning and artifacts.
A thorough grasp of artificial intelligence (AI) and machine learning, including its various forms, methods, and applications, is given in this course.
Examine how to improve learning and preserve integrity by incorporating morally sound and useful AI tools into evaluation procedures.
Study the ethical consequences of AI development and implementation, emphasizing generative AI, AI governance, and pragmatic ethical decision-making in practical contexts.
In this course, students gain the skills necessary to use Python for data science, machine learning, and foundational applications of artificial intelligence.
Featured Tools
In order to balance or improve the integration of AI in education, this course examines conversational AI technologies and provides evaluation designs.
This program instructs instructors on the ethical and successful integration of AI, while promoting innovation and critical thinking among students.
This course covers Python programming, TensorFlow for linear regression, and app development for stock market prediction.
To enhance machine learning models, this course offers fundamental understanding of artificial intelligence, machine learning methods like classification, regression, and clustering.
Acquire an extensive understanding of reinforcement learning, deep neural networks, clustering, and dimensionality reduction to effectively address real-world machine learning challenges.