Description
Hands-On Introduction to PyTorch for Machine Learning. This course provides a step-by-step, practical guide to mastering this powerful library and improving your model development skills. In today’s world where cutting-edge technology projects rely heavily on machine learning, staying up-to-date with cutting-edge tools like the open-source PyTorch framework is essential for any data scientist or machine learning engineer. This course, taught by Helen Sun, introduces you to PyTorch in a Jupyter Notebook environment and covers the basics. Participants will be thoroughly introduced to the use of Tensors and related operators, and learn how to accurately convert data between NumPy and PyTorch. The specialized part of the course focuses on the Autograd system, which enables computational tracking for model optimization. Finally, the course teaches the use of specialized peripheral libraries: TorchVision for computer vision, TorchAudio for audio processing, and TorchText for working with natural language. This comprehensive training equips learners to develop and implement diverse and effective projects in various areas of artificial intelligence using PyTorch.
What you will learn
- Master how to use Jupyter Notebook to code and run models.
- Familiarity with basic and advanced concepts in the PyTorch framework.
- Learn to work with Tensors as the main data structure in deep learning.
- How to perform mathematical and logical operators on neural network data.
- Learn the process of converting data from NumPy to PyTorch and vice versa.
- Understand the Autograd mechanism and how to record the history of calculations in the model.
- Gain skills in using TorchVision for machine vision projects.
- Learn the TorchAudio tool for processing and analyzing audio signals.
- Using TorchText to implement natural language processing (NLP) projects.
This course is suitable for people who:
- Data scientists who want to upgrade their skills with new machine learning tools.
- Machine learning engineers looking for a flexible and fast alternative to implementing complex models.
- Artificial intelligence students who want to move from a theoretical environment to a practical, project-oriented environment.
- Python programmers interested in entering the world of deep learning and neural networks.
- Data science researchers who need a powerful tool to record calculations and optimize their algorithms.
- Data analysts who want to analyze unstructured data using TorchVision or TorchText.
Course details: Hands-On Introduction to PyTorch for Machine Learning
- Publisher: LinkedIn
- Instructor: Helen Sun
- Education level: Intermediate
- Training duration: 1 hour and 10 minutes
Course headings
Course images
Sample course video
Installation Guide
After Extract, view with your favorite player.
Subtitles: English
Quality: 720p
Download link
Downloadly
Rapidgator link
File(s) password: www.downloadly.ir
File size
89 MB
