PyTorch: Deep Learning Through Object Detection

PyTorch: Deep Learning Through Object Detection, available at $34.99, has an average rating of 5, with 8 lectures, based on 1 reviews, and has 12 subscribers.

You will learn about Unlock the full potential of PyTorch. Use PyTorch and NumPy to solve complex Data Representation problems. Have a strong theoretical foundation regarding the use of Neural Networks for Object Detection Train and optimize large-scale Models Learn how to train deep learning models like a pro. With industry-standard tools This course is ideal for individuals who are People that learn by doing. or People that want to elevate their PyTorch skills. or People that want to learn how to train large Models. or People that are tired of Tutorials/Courses that consist on people reading the official documentation of a given framework It is particularly useful for People that learn by doing. or People that want to elevate their PyTorch skills. or People that want to learn how to train large Models. or People that are tired of Tutorials/Courses that consist on people reading the official documentation of a given framework.

Enroll now: PyTorch: Deep Learning Through Object Detection

Summary

Title: PyTorch: Deep Learning Through Object Detection

Price: $34.99

Average Rating: 5

Number of Lectures: 8

Number of Published Lectures: 8

Number of Curriculum Items: 8

Number of Published Curriculum Objects: 8

Original Price: $29.99

Quality Status: approved

Status: Live

What You Will Learn

Unlock the full potential of PyTorch.
Use PyTorch and NumPy to solve complex Data Representation problems.
Have a strong theoretical foundation regarding the use of Neural Networks for Object Detection
Train and optimize large-scale Models
Learn how to train deep learning models like a pro. With industry-standard tools

Who Should Attend

People that learn by doing.
People that want to elevate their PyTorch skills.
People that want to learn how to train large Models.
People that are tired of Tutorials/Courses that consist on people reading the official documentation of a given framework

Target Audiences

People that learn by doing.
People that want to elevate their PyTorch skills.
People that want to learn how to train large Models.
People that are tired of Tutorials/Courses that consist on people reading the official documentation of a given framework

Empower Your Deep Learning Journey: Become a Self-Sufficient DL Programmer with the Ability to Read and Implement Research Papers

Note: These prerequisites will ensure a solid foundation for understanding and implementing the concepts covered in the course.

Basic proficiency in Python
Basic PyTorch skills
Familiarity with NumPy for efficient data manipulation

In this course, you will:

Learn PyTorch thoroughly, including dataset objects, data loaders, transfer learning, and different gradient modes.

Acquire the ability to represent data effectively for solving complex problems.

Gain hands-on experience in coding custom loss functions.

Develop proficiency in training large models.

Join us to unlock the full potential of PyTorch and gain the practical skills necessary to excel in deep learning.

Take the Next Leap in Deep Learning: Enroll Now!

Don’t miss out on this opportunity to elevate your skills in PyTorch and master the art of deep learning. Join our course today and:

Unlock the full potential of PyTorch.
Unleash the power of PyTorch and NumPy to solve complex data representation problems with a practical example.
Develop essential skills for solving complex problems.
Gain hands-on experience with custom loss functions.
Train and optimize large-scale models.

Elevate your skills, conquer challenges, and revolutionize your data expertise today!

Course Curriculum

Chapter 1: Introduction to the Course

Lecture 1: Introduction to the course

Chapter 2: Introduction to object detection and YOLO

Lecture 1: Introduction to object detection and YOLO

Chapter 3: Generating Labels for the Dataset.

Lecture 1: Generating Labels

Chapter 4: Building the Dataset object.

Lecture 1: Building a PyTorch's Dataset object

Chapter 5: Building a custom Loss Function on PyTorch to train the YOLO model.

Lecture 1: Building a Custom Loss Function on PyTorch

Chapter 6: Building A PyTorch Model Object and implementing Transfer Learning

Lecture 1: Building a PyTorch Model

Chapter 7: Training YOLO

Lecture 1: Training YOLO and overview to useful training tools

Chapter 8: Model prediction and a few suggestions.

Lecture 1: Draw Model predictions and suggested reading material.

Instructors

Emanuel Riquelme
Deep learning and math

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5 stars: 1 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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