Machine Learning: Build Your First AI Model with Python

Machine Learning: Build Your First AI Model with Python, available at Free, has an average rating of 4.1, with 14 lectures, based on 11 reviews, and has 1587 subscribers.

You will learn about Introduction to Machine Learning: Understand the basics of machine learning, its applications, and its importance in today's world. Python Fundamentals: Learn the essential Python programming concepts and syntax required for machine learning, including variables, data types, loops, condition Data Preprocessing: Explore the crucial step of data preprocessing, including handling missing data, handling categorical variables, feature scaling, and data n Learn how to implement them using Python's scikit-learn library. This course is ideal for individuals who are Beginners: If you have little to no prior experience with machine learning or programming, this course provides a solid introduction to the field. The course explains the concepts and techniques in a beginner-friendly manner, starting from the basics and gradually building up your knowledge and skills. It is particularly useful for Beginners: If you have little to no prior experience with machine learning or programming, this course provides a solid introduction to the field. The course explains the concepts and techniques in a beginner-friendly manner, starting from the basics and gradually building up your knowledge and skills.

Enroll now: Machine Learning: Build Your First AI Model with Python

Summary

Title: Machine Learning: Build Your First AI Model with Python

Price: Free

Average Rating: 4.1

Number of Lectures: 14

Number of Published Lectures: 14

Number of Curriculum Items: 14

Number of Published Curriculum Objects: 14

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

Introduction to Machine Learning: Understand the basics of machine learning, its applications, and its importance in today's world.
Python Fundamentals: Learn the essential Python programming concepts and syntax required for machine learning, including variables, data types, loops, condition
Data Preprocessing: Explore the crucial step of data preprocessing, including handling missing data, handling categorical variables, feature scaling, and data n
Learn how to implement them using Python's scikit-learn library.

Who Should Attend

Beginners: If you have little to no prior experience with machine learning or programming, this course provides a solid introduction to the field. The course explains the concepts and techniques in a beginner-friendly manner, starting from the basics and gradually building up your knowledge and skills.

Target Audiences

Beginners: If you have little to no prior experience with machine learning or programming, this course provides a solid introduction to the field. The course explains the concepts and techniques in a beginner-friendly manner, starting from the basics and gradually building up your knowledge and skills.

Embark on an exciting journey into the world of machine learning and artificial intelligence with our comprehensive course, “Machine Learning: Build Your First AI Model with Python.” Gain the skills and knowledge needed to develop your first AI model using the powerful Python programming language and the popular scikit-learn library.

In this hands-on course, we’ll guide you step-by-step through the entire machine learning process, ensuring you grasp each concept and technique thoroughly. Whether you’re a beginner or have some programming experience, this course is designed to be accessible and engaging for all skill levels.

The course begins with a solid foundation in Python programming, ensuring you have a strong understanding of the language’s syntax and key concepts. You’ll learn about variables, data types, conditional statements, loops, functions, and more. Our instructors will provide clear explanations and practical examples to help you master Python fundamentals.

Next, we delve into the essentials of machine learning. We’ll explore the key concepts, algorithms, and evaluation metrics, empowering you to understand the inner workings of various machine learning models. Through hands-on exercises and real-world examples, you’ll gain a deep understanding of supervised and unsupervised learning, linear regression, logistic regression, decision trees, k-nearest neighbors, and more.

With a solid understanding of machine learning, we’ll then dive into the exciting world of deep learning. You’ll explore neural networks, activation functions, optimization techniques, and the foundations of popular deep learning libraries such as TensorFlow and PyTorch. Through practical projects and coding exercises, you’ll build your first deep learning models and witness their powerful capabilities.

Throughout the course, we emphasize practicality and real-world application. You’ll work on engaging projects, such as image classification, sentiment analysis, and recommendation systems, enabling you to apply your newly acquired skills to solve real-world problems. We provide guidance and support as you tackle these projects, ensuring you gain hands-on experience and build a strong portfolio of AI models.

To enhance your learning experience, we’ve integrated captivating visualizations using the matplotlib library. You’ll witness the power of data visualization as you create stunning plots and gain insights into your data and model predictions. These visualizations will deepen your understanding and make your projects visually appealing.

Our instructors are experienced machine learning practitioners who are passionate about teaching. They’ll be with you every step of the way, explaining complex concepts in a clear and approachable manner. They’ll share their valuable insights, best practices, and practical tips to help you succeed in your AI journey.

By the end of the course, you’ll have the skills and confidence to build your first AI model from scratch using Python. You’ll be equipped with a strong foundation in machine learning and deep learning, enabling you to explore more advanced topics and contribute to the exciting field of artificial intelligence.

Join us now and unlock the potential of machine learning. Enroll in “Machine Learning: Build Your First AI Model with Python” and embark on an empowering learning experience that will transform your understanding of AI and its practical applications.

Don’t miss this opportunity to dive into the fascinating world of machine learning. Enroll today and take the first step towards becoming an AI practitioner!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Installing Jupyter

Lecture 2: How to download Python files

Chapter 2: Course Contents

Lecture 1: Import datasets

Lecture 2: Import train_test_split function

Lecture 3: Import KNeighborsClassifier

Lecture 4: Import accuracy_score function

Lecture 5: Import matplotlib.pyplot

Lecture 6: Get iris data

Lecture 7: Split data

Lecture 8: create an instance of the `KNeighborsClassifier` class

Lecture 9: training a k-nearest neighbors classifier

Lecture 10: make predictions on the test set

Lecture 11: By comparing the predicted labels to the true labels and calculating the accurac

Lecture 12: Create a scatter plot

Instructors

Abdurrahman TEKIN
PhD student

Rating Distribution

1 stars: 1 votes
2 stars: 0 votes
3 stars: 0 votes
4 stars: 7 votes
5 stars: 3 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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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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