Machine Learning Fundamental of Python Machine Learning

Machine Learning – Fundamental of Python Machine Learning, available at $19.99, has an average rating of 4.15, with 22 lectures, based on 234 reviews, and has 28136 subscribers.

You will learn about The Machine Learning Process Standard Deviation Linear Regression Polynomial Regression Multiple Regression Hierarchical Clustering Logistic Regression Bootstrap Aggregation Cross Validation This course is ideal for individuals who are Anyone interested in Machine Learning or Beginners Who want to Learn Machine Learning It is particularly useful for Anyone interested in Machine Learning or Beginners Who want to Learn Machine Learning.

Enroll now: Machine Learning – Fundamental of Python Machine Learning

Summary

Title: Machine Learning – Fundamental of Python Machine Learning

Price: $19.99

Average Rating: 4.15

Number of Lectures: 22

Number of Published Lectures: 22

Number of Curriculum Items: 22

Number of Published Curriculum Objects: 22

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

The Machine Learning Process

Standard Deviation

Linear Regression

Polynomial Regression

Multiple Regression

Hierarchical Clustering

Logistic Regression

Bootstrap Aggregation

Cross Validation

Who Should Attend

Anyone interested in Machine Learning

Beginners Who want to Learn Machine Learning

Target Audiences

Anyone interested in Machine Learning

Beginners Who want to Learn Machine Learning

Are you ready to learn on a journey into the captivating world of machine learning using Python? Welcome to “Machine Learning – Fundamentals of Python Machine Learning,” your gateway to understanding and applying the core principles of machine learning.

Machine learning is transforming industries, from healthcare to finance, and Python is at the forefront of this revolution. Whether you’re a budding data scientist, aspiring machine learning engineer, or simply curious about the potential of AI, this course will equip you with the foundational knowledge and practical skills to harness the power of Python for machine learning.

Key Learning Objectives:

Introduction to Machine Learning: Get a comprehensive overview of machine learning, its significance, and the Python ecosystem’s role in the field.

Python for Machine Learning: Learn the basics of Python programming, data structures, and libraries essential for machine learning.

Model Evaluation and Selection: Discover techniques for evaluating machine learning models and selecting the best model for your tasks.

Feature Engineering:Master the art of feature selection and engineering to enhance the performance of your machine learning models.

Why Choose This Course?

Comprehensive Curriculum: This course is designed to take you from a machine learning novice to a proficient practitioner, ensuring you have a deep understanding of the fundamentals.

Hands On Learning: Practice your skills with coding exercises, hands-on projects, and machine learning challenges that replicate real-world scenarios.

Expert Instruction: Benefit from the guidance of experienced instructors who have worked on machine learning projects and are passionate about sharing their knowledge.

Lifetime Access: Enroll once and have lifetime access to the course materials, ensuring your skills stay up to date with the latest developments in machine learning.

Unlock the potential of Python in the world of machine learning. Enroll today in “Machine Learning – Fundamentals of Python Machine Learning” and acquire the knowledge and skills you need to excel in the exciting field of machine learning. Don’t miss this opportunity to become a proficient machine learning practitioner.

Your journey to mastering machine learning with Python starts now!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Mean, Median and Mode

Lecture 2: Standard Deviation

Lecture 3: Percentiles

Lecture 4: Data Distribution

Lecture 5: Normal Data Distribution

Lecture 6: Scatter Plot

Lecture 7: Linear Regression

Lecture 8: Polynomial Regression

Lecture 9: Multiple Regression

Lecture 10: Scale

Lecture 11: Train or Test data

Lecture 12: Decision Tree

Lecture 13: Confusion Matrix

Lecture 14: Hierarchical Clustering

Lecture 15: Logistic Regression

Lecture 16: Grid Search

Lecture 17: Categorical Data

Lecture 18: K-Means

Lecture 19: Bootstrap Aggregation

Lecture 20: Cross Validation

Lecture 21: AUC-ROC Curve

Lecture 22: K-nearest neighbors

Instructors

Sara Academy
Programmer | Android Developer | Web Designer | Instructor

Rating Distribution

1 stars: 10 votes

2 stars: 9 votes

3 stars: 37 votes

4 stars: 85 votes

5 stars: 93 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!