The Power of Machine Learning (2023) beginner bootcamp

The Power of Machine Learning (2023) beginner bootcamp, available at $19.99, with 11 lectures.

You will learn about Introduction to Machine Learning The Math Behind Machine Learning Supervised Leaning Unsupervised Learning Reinforcement Learning Overfitting and Underfitting Model Evaluation Feature Engineering Deep Learning Real-World Applications of Machine Learning This course is ideal for individuals who are This course is intended for individuals with little to no prior experience in machine learning who are looking to learn about the basics of this field. This includes aspiring data scientists, software engineers, and anyone who wants to understand how machines can learn from data. A basic understanding of mathematics and programming concepts will be helpful but not necessary. The course is designed to be hands-on and action-oriented, with a focus on helping learners apply the concepts they learn to real-world problems. It is particularly useful for This course is intended for individuals with little to no prior experience in machine learning who are looking to learn about the basics of this field. This includes aspiring data scientists, software engineers, and anyone who wants to understand how machines can learn from data. A basic understanding of mathematics and programming concepts will be helpful but not necessary. The course is designed to be hands-on and action-oriented, with a focus on helping learners apply the concepts they learn to real-world problems.

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Summary

Title: The Power of Machine Learning (2023) beginner bootcamp

Price: $19.99

Number of Lectures: 11

Number of Published Lectures: 11

Number of Curriculum Items: 11

Number of Published Curriculum Objects: 11

Original Price: $29.99

Quality Status: approved

Status: Live

What You Will Learn

Introduction to Machine Learning
The Math Behind Machine Learning
Supervised Leaning
Unsupervised Learning
Reinforcement Learning
Overfitting and Underfitting
Model Evaluation
Feature Engineering
Deep Learning
Real-World Applications of Machine Learning

Who Should Attend

This course is intended for individuals with little to no prior experience in machine learning who are looking to learn about the basics of this field. This includes aspiring data scientists, software engineers, and anyone who wants to understand how machines can learn from data. A basic understanding of mathematics and programming concepts will be helpful but not necessary. The course is designed to be hands-on and action-oriented, with a focus on helping learners apply the concepts they learn to real-world problems.

Target Audiences

This course is intended for individuals with little to no prior experience in machine learning who are looking to learn about the basics of this field. This includes aspiring data scientists, software engineers, and anyone who wants to understand how machines can learn from data. A basic understanding of mathematics and programming concepts will be helpful but not necessary. The course is designed to be hands-on and action-oriented, with a focus on helping learners apply the concepts they learn to real-world problems.

This course is a comprehensive and intensive introduction to the field of machine learning. It covers the fundamental concepts and techniques used in the field and will provide you with a solid foundation for further study and exploration. The course covers a wide range of topics, including supervised and unsupervised learning, linear and logistic regression, decision trees and random forests, clustering, and model evaluation and selection. These topics are all essential for anyone looking to get a comprehensive understanding of machine learning and how to apply these techniques to real-world problems.

The course is designed for those with little to no prior experience in machine learning and will provide you with the skills and knowledge you need to get started in the field. You will understand how real-world data and common programming tools are used such as Python and scikit-learn to apply the algorithms you learn about. This hands-on approach to learning will ensure that you have a solid understanding of the key principles and methods of machine learning and that you are able to apply these to tackle a range of practical problems.

Whether you are a beginner looking to start your journey in the field of machine learning or a seasoned professional looking to expand your knowledge and skills, this course is designed to provide you with the knowledge and expertise you need to succeed. With a strong focus on hands-on learning, you will have the opportunity to put your new skills into practice and gain a solid understanding of the key concepts and techniques used in machine learning.

Course Curriculum

Chapter 1: Chapter 1

Lecture 1: Introduction

Chapter 2: Chapter 2

Lecture 1: The Math Behind Machine Learning

Chapter 3: Chapter 3

Lecture 1: Supervised Learning

Chapter 4: Chapter 4

Lecture 1: Unsupervised Learning

Chapter 5: Chapter 5

Lecture 1: Reinforcement Learning

Chapter 6: Chapter 6

Lecture 1: Overfitting and Underfitting

Chapter 7: Chapter 7

Lecture 1: Model Evaluation

Chapter 8: Chapter 8

Lecture 1: Feature Engineering

Chapter 9: Chapter 9

Lecture 1: Deep Learning

Chapter 10: Chapter 10

Lecture 1: Real-World Applications of Machine Learning

Chapter 11: Knowledge Test

Lecture 1: questions

Instructors

Joel Morris
Technology

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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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