Obesity Prediction Using Machine Learning Practical Approach

Obesity Prediction Using Machine Learning Practical Approach, available at Free, with 7 lectures, 1 quizzes, and has 238 subscribers.

You will learn about Understanding of Obesity and Its Implications – Gain comprehensive knowledge about obesity, including its causes, health implications, and the early detection. Proficiency in Machine Learning Techniques – Develop the ability to apply various machine learning algorithms to predict Obesity. Hands-on Experience with Real-world Data – Acquire practical experience working with real-world health data, learning to clean, process, and analyze dataset. Implementation of Predictive Models – Learn to implement, fine-tune, and deploy machine learning models using popular tools and libraries to predict obesity. This course is ideal for individuals who are This course is meant for learner who don't have knowledge about Machine Learning. It is particularly useful for This course is meant for learner who don't have knowledge about Machine Learning.

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Summary

Title: Obesity Prediction Using Machine Learning Practical Approach

Price: Free

Number of Lectures: 7

Number of Quizzes: 1

Number of Published Lectures: 7

Number of Published Quizzes: 1

Number of Curriculum Items: 8

Number of Published Curriculum Objects: 8

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

Understanding of Obesity and Its Implications – Gain comprehensive knowledge about obesity, including its causes, health implications, and the early detection.
Proficiency in Machine Learning Techniques – Develop the ability to apply various machine learning algorithms to predict Obesity.
Hands-on Experience with Real-world Data – Acquire practical experience working with real-world health data, learning to clean, process, and analyze dataset.
Implementation of Predictive Models – Learn to implement, fine-tune, and deploy machine learning models using popular tools and libraries to predict obesity.

Who Should Attend

This course is meant for learner who don't have knowledge about Machine Learning.

Target Audiences

This course is meant for learner who don't have knowledge about Machine Learning.

The online course “Obesity Prediction Using Machine Learning: A Practical Approach” offers a comprehensive introduction to leveraging machine learning techniques for predicting obesity. Students will learn the fundamentals of obesity, including its causes, health implications, and the importance of early prediction. The course covers essential machine learning concepts and their applications in healthcare, focusing on obesity data. Participants will gain hands-on experience with Python libraries such as Pandas, Scikit-learn, and TensorFlow for data preprocessing, model building, and evaluation. Real-world datasets will be used to teach data cleaning, encoding, and outlier removal techniques. Students will also explore advanced topics like feature engineering, correlation analysis, and model tuning to improve prediction accuracy. By the end of the course, learners will be able to interpret model results and make data-driven decisions for obesity management. The course is designed for both beginners and those with some experience in data science, providing practical skills that are directly applicable to real-world health challenges.

Additionally, the course includes quizzes and assignments to reinforce learning, as well as a final project where students will create and evaluate their own obesity prediction model, ensuring a thorough and practical understanding of the subject matter. The interactive nature of the course ensures that students can apply theoretical knowledge to practical scenarios, enhancing their learning experience. The course also provides continuous support through discussion forums and live Q&A sessions, enabling students to resolve their doubts and interact with peers. With comprehensive coverage of machine learning techniques and their application to obesity prediction, this course equips students with the knowledge and skills required to address one of the most pressing health issues of our time. Students will emerge from the course with a robust understanding of how to use machine learning tools to analyze health data and contribute to effective obesity prevention and management strategies.

Course Curriculum

Chapter 1: Obesity Prediction Using Machine Learning

Lecture 1: Introduction Obesity

Lecture 2: Obesity Control

Lecture 3: Machine Learning with Obesity

Lecture 4: Stake Holders of Machine Learning for Obesity Prediction

Lecture 5: Real Time Dataset, Libraries and Dataset Specifications – Handson

Lecture 6: Data Preprocessing, Encoding, Removing Outliers and Correlation – Handson

Lecture 7: Data Seperation, Scaling, Model Building, and Performance Evaluation – Handson

Instructors

Soubraylu Sivakumar
Instructor in Udemy

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Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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