PyTorch Essential Training: Deep Learning

Focused View

Terezija Semenski

1:21:46

45 View

01 - Introduction

01 - Deep learning with PyTorch.mp4

00:31

02 - What you should know.mp4

01:17

03 - Tour of CoderPad.mp4

03:08

02 - 1. PyTorch Overview and Introduction to Google Colaboratory

01 - Introduction to deep learning.mp4

04:20

02 - Why should you use PyTorch.mp4

02:01

03 - Google Colaboratory basics.mp4

03:27

03 - 2. Tensors

01 - Introduction to tensors.mp4

03:24

02 - Creating a tensor CPU example.mp4

01:48

03 - Creating a tensor GPU example.mp4

01:46

04 - Moving tensors between CPUs and GPUs.mp4

02:10

04 - 3. Creating Tensors

01 - Different ways to create tensors.mp4

03:39

02 - Tensor attributes.mp4

02:11

03 - Tensor data types.mp4

03:16

04 - Creating tensors from random samples.mp4

02:41

05 - Creating tensors like other tensors.mp4

02:05

06 - Solution Create tensors.mp4

01:49

05 - 4. Manipulate Tensors

01 - Tensor operations.mp4

04:35

02 - Mathematical functions.mp4

03:36

03 - Linear algebra operations.mp4

03:56

04 - Automatic differentiation (Autograd).mp4

06:05

05 - Solution Split tensors to form new tensors.mp4

01:53

06 - 5. Developing a Deep Learning Model

01 - Introduction to the DL training process.mp4

02:35

02 - Data preparation.mp4

01:37

03 - Data loading.mp4

02:37

04 - Data transforms.mp4

02:40

05 - Data batching.mp4

02:55

06 - Model development and training.mp4

04:46

07 - Validation and testing.mp4

04:10

07 - Conclusion

01 - Next steps.mp4

00:48

Description

PyTorch is the most flexible and expressive library for deep learning, and offers simple Python API, GPU support, and flexibility. It’s designed to load data, apply transforms, and build deep learning models with just a few lines of code. Many machine learning developers and researchers use PyTorch to accelerate deep learning research, experimentation, and prototyping. In this course, software developer Terezija Semenski teaches you the important features of PyTorch with a hands-on approach to help you develop the skills you need to dive into your deep learning projects.

This course includes Code Challenges powered by CoderPad. Code Challenges are interactive coding exercises with real-time feedback, so you can get hands-on coding practice alongside the course content to advance your programming skills.

More details

User Reviews

Rating

average 0

Total votes0

Focused display

Python

Deep Learning

Terezija Semenski

Instructor's Courses

I help busy people learn to code without spending hours on searching Google and Stackoverflow. Mathematician and Software Developer with a business mind, a learning mindset, and a passion for people. Currently working as a freelance Educator and Software Developer. I’m also preparing my 8th online course. My previous experience includes working as Software Developer and QA in startup on educational, financial and banking app development projects and in the education sector as IT and Mathematics Teacher.

Linkedin Learning

View courses Linkedin Learning

LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.