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[Free] Fundamentals Of Machine Learning Regression

Master the Fundamentals of Regression Techniques in Machine Learning: SciKit Learn and Pandas Essentials – Free Course

Added on July 6, 2024 Development 3 min read

What you’ll learn

• Grasp the fundamental concepts of regression and its importance in predicting continuous outcomes
• Implement and evaluate models to solve real-world problems
• Learn data preprocessing techniques, including data cleaning and transformations using pandas
• Learn to evaluate regression models using metrics such as R² Score to assess model accuracy and performance.
• Understand the importance of splitting data into training and testing sets to validate model performance
• Learn how to build and implement linear regression models using SciKit Learn to predict target variables based on input features.
• Understand the key differences between classification and regression tasks, including their objectives and different real world applications
• Learn to build and implement decision tree models for regression using SciKit-Learn
• ain knowledge of SVMs and how to apply them for regression tasks, including the concepts of hyperplanes and margins.

Requirements

• Beginnner Python Experience Helps

Description

What You’ll Learn:

• Core Regression Algorithms: Delve into the principles and applications of linear regression, support vector machine and decision trees.

• Model Evaluation Techniques: Learn to evaluate your models’ performance using essential metrics, ensuring accuracy and reliability.

• Data Preprocessing with pandas: Acquire the basic skills to clean and transform data, a vital step in any machine learning project.

• Hands-On Practice: Engage in interactive code-along sessions to apply theoretical knowledge and gain practical experience.

Why This Course?

Our course offers high-quality content designed to be both comprehensive and engaging. Each lesson features meticulously crafted presentations and interactive code-along sessions, ensuring you not only understand the theory but can also implement it effectively.

Who Should Join:

• Beginners in Machine Learning: This course is perfect for those new to the field, providing a solid foundation in regression techniques and data preprocessing.

• Experienced Programmers: Expand your programming expertise by integrating basic machine learning concepts and practices.

• Data Science Enthusiasts: Enhance your data analysis skills and learn to build effective regression models.

• Students and Professionals: Apply machine learning regression in academic projects or professional scenarios to solve real-world problems.

Course Highlights:

• High-Quality Presentations: Our lectures are designed to simplify complex concepts, making them accessible and engaging.

• Interactive Code-Alongs: Follow along with practical coding sessions that reinforce your learning through hands-on practice.

• Comprehensive Coverage: From theoretical foundations to practical implementations, this course covers all aspects of machine learning regression.

Don’t miss the opportunity to adapt to the AI-driven future. Enroll in Fundamentals of Machine Learning Regression today and take the first step towards mastering machine learning regression techniques.