Introduction to Machine Learning with Python
Master Python programming for machine learning, covering supervised and unsupervised learning, deep learning, and neural networks for beginners.
Master Python programming for machine learning, covering supervised and unsupervised learning, deep learning, and neural networks for beginners.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Python: A Guided Journey from Introduction to Application Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
3.3
(13 ratings)
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What you'll learn
Apply Python programming to machine learning tasks
Implement supervised and unsupervised learning models
Create deep learning and neural network solutions
Process and analyze image data effectively
Develop generative adversarial networks
Skills you'll gain
This course includes:
2.5 Hours PreRecorded video
9 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course introduces machine learning concepts using Python programming. Students learn about supervised and unsupervised learning algorithms, including perceptrons, linear regression, k-nearest neighbors, and support vector machines. The curriculum covers advanced topics like deep learning, image processing, and generative adversarial networks (GANs). Practical implementation focuses on creating and training machine learning models for real-world applications.
Course Introduction
Module 1 · 11 Minutes to complete
Introduction to Machine Learning
Module 2 · 4 Hours to complete
More Supervised Learning Algorithms
Module 3 · 4 Hours to complete
Advanced Machine Learning Topics
Module 4 · 3 Hours to complete
Fee Structure
Instructor
Assistant Teaching Professor
Adwith Malpe is a Computer Engineer with a Master’s degree in Computer Engineering and a Bachelor’s in Computer Systems Engineering from Arizona State University. His industry experience spans both the financial and aerospace sectors, with a strong focus on Computer Science.
Testimonials
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3.3 course rating
13 ratings
Frequently asked questions
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