Project – Predicting Stars, Galaxies and Quasars with ML
Project – Predicting Stars, Galaxies and Quasars with ML, available at $19.99, has an average rating of 3.92, with 14 lectures, 3 quizzes, based on 43 reviews, and has 1287 subscribers.
You will learn about Learn about Celestial Objects Analysing stars, galaxies and quasars dataset Learn Machine Learning Techniques Resume worthy space related complete project This course is ideal for individuals who are Whoever interested in Astronomy and Astrophysics It is particularly useful for Whoever interested in Astronomy and Astrophysics.
Enroll now: Project – Predicting Stars, Galaxies and Quasars with ML
Summary
Title: Project – Predicting Stars, Galaxies and Quasars with ML
Price: $19.99
Average Rating: 3.92
Number of Lectures: 14
Number of Quizzes: 3
Number of Published Lectures: 14
Number of Published Quizzes: 3
Number of Curriculum Items: 17
Number of Published Curriculum Objects: 17
Original Price: ₹799
Quality Status: approved
Status: Live
What You Will Learn
- Learn about Celestial Objects
- Analysing stars, galaxies and quasars dataset
- Learn Machine Learning Techniques
- Resume worthy space related complete project
Who Should Attend
- Whoever interested in Astronomy and Astrophysics
Target Audiences
- Whoever interested in Astronomy and Astrophysics
Welcome to “Project – Predicting Stars, Galaxies, and Quasars with ML”, a specialized course where the realms of astronomy and machine learning intersect to create a unique and compelling learning experience.
About This Course: Are you fascinated by the universe and the treasures it holds? Do you have a passion for data science and its limitless possibilities? This course is designed to bring these two worlds together by teaching you how to apply machine learning techniques to classify cosmic bodies such as stars, galaxies, and quasars.
What You’ll Learn:
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Foundational Astronomy: Get to grips with the astronomical basics necessary for understanding the data you’ll be working with, including the characteristics of different celestial objects.
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Data Handling Skills: Learn how to preprocess, clean, and manipulate large datasets typical of astronomical data collection efforts.
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Machine Learning Techniques: Dive deep into machine learning algorithms, understanding how they can be trained to categorize vast and complex cosmic datasets.
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Model Evaluation: Master the techniques for validating the performance of your machine learning models, ensuring accurate and reliable classification results.
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Real-world Application: Apply your skills to a project that mirrors real-world tasks faced by astrophysicists and data scientists in the field.
Who This Course Is For: This course is ideal for data scientists, machine learning enthusiasts, and anyone with a curiosity about astronomy and how modern technology can be used to decipher it. Whether you’re looking to apply machine learning to a new domain or you’re an amateur astronomer eager to explore how data science can further your observations, this course will provide the knowledge and hands-on experience you’re looking for.
By the End of This Course: You will have completed a project that not only demonstrates your ability to handle complex datasets but also your capability to extract meaningful insights from the noise of the cosmos. You will have the confidence to tackle similar challenges, the skills to further your study, and the foundational knowledge to pursue more advanced work in either field.
Prepare to embark on a journey of discovery that will take you from the classroom to the cosmos, as you learn to harness the power of machine learning to unlock secrets of the universe that have puzzled humanity for centuries.
Enroll now and start your adventure into the cosmos with the power of machine learning!
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction and Problem Statement
Lecture 2: Stars, Galaxies and Quasars
Lecture 3: Peeking into Dataset
Lecture 4: Importing Necessary Libraries and Modules
Chapter 2: Data Analysis
Lecture 1: Exploring the Dataset
Lecture 2: Performing Label Encoding on Class Column
Lecture 3: Splitting the Dataset into Training and Testing (Data Leakage)
Lecture 4: Using Seaborn for some Visual Analysis
Chapter 3: Machine Learning
Lecture 1: Understand and Build Decision Tree Classifier
Lecture 2: Understand and Build Logistic Regression for Classification
Lecture 3: Gist on KNN and Building it (Link for Exoplanets Udemy)
Lecture 4: Train the ML models and make them predict on Test Data
Lecture 5: Understand the Classification Report and Evaluate the ML Models
Lecture 6: Conclusion
Instructors
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Spartificial Innovations
AI and Space Science Institute
Rating Distribution
- 1 stars: 0 votes
- 2 stars: 1 votes
- 3 stars: 16 votes
- 4 stars: 14 votes
- 5 stars: 12 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
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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