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CS 445/545 Machine Learning Spring, 2013 Homework 1: Decision Trees Due Wednesday, April 17, 2pm In this homework assignment you will experiment with C4.5, an implementation of ID3 written by Ross

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How to fill out cs 445545 machine learning:

1. Start by understanding the course requirements: Read the course syllabus and familiarize yourself with the learning objectives, assignments, and grading criteria.
2. Attend all lectures and take thorough notes: Machine learning can be a complex subject, so it's essential to pay attention in class and take detailed notes to better understand the concepts being taught.
3. Complete assigned readings and supplementary materials: Professors often assign readings and provide additional resources to enhance your understanding of the material. Make sure to complete all assigned readings and explore supplementary materials to gain a comprehensive understanding of machine learning.
4. Engage in active learning: Rather than passively absorbing information, actively engage with the material. This can include asking questions during lectures, participating in discussions, and seeking clarification when needed.
5. Practice coding: Machine learning involves implementing algorithms and writing code. Familiarize yourself with programming languages commonly used in machine learning, such as Python or R, and practice coding exercises and projects related to the course.
6. Complete assignments and projects: Stay on top of all assignments and projects. Allocate sufficient time and effort to complete them, ensuring you understand the underlying concepts and methodologies.
7. Seek help when needed: If you encounter difficulties, don't hesitate to seek help. Reach out to your professor, teaching assistants, or classmates to clarify doubts or discuss challenging concepts.

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cs 445545 machine learning is a course that covers various algorithms and techniques used in teaching machines to learn from data and make predictions or decisions without being explicitly programmed.

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The purpose of cs 445545 machine learning is to teach students how to build and apply machine learning models to solve real-world problems, improve decision making, and gain insights from data.

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Students must report their progress on assignments, projects, and exams, along with any challenges faced, insights gained, and lessons learned during the course.

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