Intro to Machine Learning with PyTorch

Online Course

Udacity

What is the course about?
Prerequisites & Facts
Cost, Certificate & Degree
Reviews & Experiences

What is the course about?

Intro to Machine Learning with PyTorch

The course Intro to Machine Learning with PyTorch is an online class provided by Udacity. It may be possible to receive a verified certification or use the course to prepare for a degree.

Learn foundational machine learning techniques — from data manipulation to unsupervised and supervised algorithms.

Course description

Intro to Machine Learning with PyTorch
3 months (10 hrs/week)

Learn foundational machine learning algorithms, starting with data cleaning and supervised models. Then, move on to exploring deep and unsupervised learning. At each step, get practical experience by applying your skills to code exercises and projects.
This program is intended for students with experience in Python, who have not yet studied Machine Learning topics.
Learn foundational machine learning techniques – from data manipulation to unsupervised and supervised algorithms in PyTorch and scikit-learn.
To optimize your chances of success in this program, we recommend intermediate Python programming knowledge and basic knowledge of probability and statistics.See detailed requirements.
In this lesson, you will learn about supervised learning, a common class of methods for model construction.
In this lesson, you’ll learn the foundations of neural network design and training in PyTorch.
In this lesson, you will learn to implement unsupervised learning methods for different kinds of problem domains.
Learn Python skills in the Intro to Programming Nanodegree program or the AI Programming for Python Nanodegree program.
Learn Python skills in the Intro to Programming Nanodegree program or the AI Programming for Python Nanodegree program.
LinkedIn ranked AI Specialist as the #1 Emerging Job in 2020, with 74% annual job growth.

Supervised Learning
In this lesson, you will learn about supervised learning, a common class of methods for model construction.
Find Donors for CharityML
Deep Learning
In this lesson, you’ll learn the foundations of neural network design and training in PyTorch.
Build an Image Classifier
Unsupervised Learning
In this lesson, you will learn to implement unsupervised learning methods for different kinds of problem domains.
Create Customer Segments
To optimize your chances of success in this program, we recommend intermediate Python programming knowledge and basic knowledge of probability and statistics.

Machine learning is changing countless industries, from health care to finance to market predictions. Currently, the demand for machine learning engineers far exceeds the supply. In this program, you’ll apply machine learning techniques to a variety of real-world tasks, such as customer segmentation and image classification. This program is designed to teach you foundational machine learning skills that data scientists and machine learning engineers use day-to-day.
This program emphasizes practical coding skills that demonstrate your ability to apply machine learning techniques to a variety of business and research tasks. It is designed for people who are new to machine learning and want to build foundational skills in machine learning algorithms and techniques to either advance within their current field or position themselves to learn more advanced skills for a career transition.
This program assumes that you have had several hours of Python programming experience. Other than that, the only requirement is that you have a curiosity about machine learning. Do you want to learn more about recommendation systems or voice assistants and how they work? If so, then this program is right for you.
What is the difference between Intro to Machine Learning with PyTorch, and Intro to Machine Learning with TensorFlow Nanodegree programs?
Both Nanodegree programs begin with the scikit-learn machine learning library, before pivoting to either PyTorch or TensorFlow in the Deep Learning sections.
The only difference between the two programs is the deep learning framework utilized for Project 2. As such, there are accompanying lessons in each respective Nanodegree program that train you to develop machine learning models in that deep learning framework. You will complete the same project, Create an Image Classifier, in both Nanodegree programs – in PyTorch in Intro to Machine Learning with PyTorch, and in TensorFlow for Intro to Machine Learning with TensorFlow.

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Prerequisites & Facts

Intro to Machine Learning with PyTorch

Course Topic

Personal Success, Teacher Training, Teaching & Academics

University, College, Institution

Udacity

Course Skill Level

see course summary

Course Language

English

Place of class

Online, self-paced (see curriculum for more information)

Degree

Certificate

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Degree & Cost

Intro to Machine Learning with PyTorch

To obtain a verified certificate from Udacity you have to finish this course or the latest version of it, if there is a new edition. The class may be free of charge, but there could be some cost to receive a verified certificate (399 USD) or to access the learning materials. The specifics of the course may have been changed, please consult the provider to get the latest quotes and news.

Udacity

Intro to Machine Learning with PyTorch

provided by Udacity

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School: Udacity

Topic: Computer Science, Machine Learning, PyTorch

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