Machine Learning in 30 mins: fast practice
Machine Learning in 30 mins: fast practice, available at Free, has an average rating of 4.5, with 13 lectures, based on 60 reviews, and has 1740 subscribers.
You will learn about How to use machine learning to solve real-world problems How to build and evaluate machine learning models in Python Different types of machine learning algorithms the steps you should learn to build any machine learning model This course is ideal for individuals who are This course is for absolute beginners in machine learning. You will learn the basics of machine learning, including supervised learning. You will also learn how to build and evaluate machine learning models using Python. It is particularly useful for This course is for absolute beginners in machine learning. You will learn the basics of machine learning, including supervised learning. You will also learn how to build and evaluate machine learning models using Python.
Enroll now: Machine Learning in 30 mins: fast practice
Summary
Title: Machine Learning in 30 mins: fast practice
Price: Free
Average Rating: 4.5
Number of Lectures: 13
Number of Published Lectures: 13
Number of Curriculum Items: 13
Number of Published Curriculum Objects: 13
Original Price: Free
Quality Status: approved
Status: Live
What You Will Learn
- How to use machine learning to solve real-world problems
- How to build and evaluate machine learning models in Python
- Different types of machine learning algorithms
- the steps you should learn to build any machine learning model
Who Should Attend
- This course is for absolute beginners in machine learning. You will learn the basics of machine learning, including supervised learning. You will also learn how to build and evaluate machine learning models using Python.
Target Audiences
- This course is for absolute beginners in machine learning. You will learn the basics of machine learning, including supervised learning. You will also learn how to build and evaluate machine learning models using Python.
This course is a comprehensive introduction to machine learning for beginners. You will learn the basics of machine learning, including supervised learning. You will also learn how to build and evaluate machine learning models in Python.
In the first section of the course, you will learn what machine learning is and how it works. You will also learn about the different types of machine learning algorithms and their applications.
In the second section of the course, you will learn about supervised learning. Supervised learning is a type of machine learning in which the algorithm is trained on a set of labeled data. The algorithm learns to predict the output for new data based on the patterns in the training data.
In the third section of the course, you will learn about unsupervised learning. Unsupervised learning is a type of machine learning in which the algorithm is trained on a set of unlabeled data. The algorithm learns to identify patterns in the data without being told what the patterns are.
In the fourth section of the course, you will learn about reinforcement learning.
In the fifth section of the course, you will learn how to build and evaluate machine learning models in Python. You will learn how to use popular Python libraries such as NumPy, pandas, and scikit-learn to build and evaluate different types of machine learning models.
By the end of this course, you will have a solid understanding of the basics of machine learning and you will be able to build and evaluate machine learning models in Python. You will also be able to apply machine learning to solve real-world problems.
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these are the main things will be explained in this course
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Machine Learning for Beginners
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Learn Machine Learning Step-by-Step
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Machine Learning for Real-World Applications
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Introduction to Machine Learning
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Supervised Learning Algorithms
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Machine Learning for Medical Diagnosis
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Machine Learning for Financial Trading
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Machine Learning for the Future
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3 Machine Learning Projects
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Machine Learning Algorithms classification and regression
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How Machine Learning Works
Course Curriculum
Chapter 1: Introduction
Lecture 1: Machine Learning Crash Course For Absolute Beginners 2024
Lecture 2: What we'll cover in this course
Chapter 2: The basics of machine learning
Lecture 1: The Tools and Libraries we will use.
Lecture 2: Step-by-Step Guide to Building Models
Chapter 3: Build Your First Machine Learning Model
Lecture 1: Diabetes Prediction Project
Lecture 2: Import The Dependencies.
Lecture 3: Data Collection & preprocessing
Lecture 4: Data Splitting
Lecture 5: Create A Model & Train It
Lecture 6: Prediction and Evaluation
Chapter 4: Build Your Second Machine Learning Model
Lecture 1: Wine Quality Prediction Model
Lecture 2: Building the model
Chapter 5: Third Project
Lecture 1: EUR/USD Prediction Project
Instructors
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Mahmood Abdulkareem
Udemy instructor
Rating Distribution
- 1 stars: 3 votes
- 2 stars: 5 votes
- 3 stars: 6 votes
- 4 stars: 19 votes
- 5 stars: 27 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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