Table of Contents
Best PyTorch Courses 2023
Intro to Machine Learning with PyTorch
This nanodegree program is meant to teach you the fundamentals of machine learning so that you can advance your career in AI and ML. Participating in this program will offer you with in-depth knowledge of supervised learning, neural network design fundamentals, and PyTorch training. You will also learn about deep learning algorithms, which are an important aspect of machine learning. The curriculum was developed by Udacity specialist educators who are well-versed in ML algorithms. If you have any questions about the program material, you will receive full assistance and support from the teachers during the course.
You will:
Discover the fundamental principles and techniques of machine learning, including data manipulation, unsupervised and supervised algorithms, and much more.
Discover how to use unsupervised learning approaches to solve a variety of challenges in any application.
Master ML skills by working on real-world projects in collaboration with industry experts and top-tier firms.
With the program, you will receive customized career coaching services to assist you in choosing the proper path after completing this course.
A learning plan that is adaptable to your daily schedule and work-life balance.
PyTorch for Deep Learning with Python Bootcamp
Welcome to the best online courses for learning Deep Learning with Python and PyTorch! PyTorch is an open source deep learning platform that provides a seamless path from research prototyping to production deployment. It is fast becoming one of the most popular deep learning frameworks for Python programming language. Deep integration into Python allows the use of popular libraries and packages to easily write neural network layers in Python. A rich ecosystem of tools and libraries extends PyTorch framework and supports development in computer vision, NLP and more.
This Pytorch tutorial focuses on balancing important theoretical concepts with hands-on exercises and projects that allow you to learn how to apply the concepts from the course to your own data sets! When you register for this course, you will have access to carefully laid out notebooks that explain the concepts in an easy to understand manner, including code and side-by-side explanations. You’ll also have access to our slides that explain the theory through easy-to-understand visualizations. In this course, we’ll teach you everything you need to know to get started with modern Deep Learning with Pytorch, including:
NumPy
Pandas
Machine learning theory
Separation of test / train / validation data
Model evaluation – Regression and classification tasks
Unsupervised learning tasks
Tensors with PyTorch
Neural network theory
Will perceive
Networks
Activation functions
Cost / loss functions
Backpropagation
Gradients
Artificial neural networks
Convolutional neural networks
Recurrent neural networks
By the end of this course, you will be able to create a wide variety of deep learning models to solve your own problems with your own custom dataset.
You will learn:
Learn how to use NumPy to format data in tables
Use pandas for data manipulation and cleansing
Learn the principles of classical machine learning theory
Use PyTorch Deep Learning Library for image classification
Using PyTorch with Recurrent Neural Networks for Sequence Time Series Data
Create cutting-edge deep learning models to work with tabular data
This is the best PyTorch course in 2023.
Deep Neural Networks with PyTorch
by Joseph Santarcangelo will show you how to use Pytorch to create deep learning models. The lecture will begin with tensors and the Automatic differentiation module in Pytorch. Then, in each section, new models will be covered, beginning with essentials such as Linear Regression and logistic/softmax regression. Feedforward deep neural networks are followed by the involvement of multiple activation functions, normalization, and dropout layers. Following that, Convolutional Neural Networks and Transfer Learning will be discussed. Finally, a number of different Deep Learning approaches will be discussed.
You will:
• be able to explain and apply their understanding of Deep Neural Networks and associated machine learning methods
• be familiar with Python packages such as PyTorch for Deep Learning applications
• use PyTorch to create Deep Neural Networks
Modern Deep Convolutional Neural Networks with PyTorch
The course consists of 4 blocks:
Introductory section, where I remind you, what is linear layers, SGD and how to train deep networks.
Convolution section, where we discuss convolutions, its parameters, advantages and disadvantages.
Regularization and Standardization section, where I share with you useful tips and tricks in Deep Learning.
Fine tuning, transfer learning, modern data sets and architectures
You will learn
Convolutional neural networks
Image processing
Advance deep learning techniques
Regularization, standardization
Transfer learning
PyTorch for Deep Learning and Computer Vision
PyTorch has quickly become one of the most transformative executives in the deep learning field. Since its launch, PyTorch has completely changed the landscape in the field of deep learning due to its flexibility and ease of use when creating deep learning models. Deep Learning jobs are among the highest paying in the development world. This course is intended to take you from comprehensive basics to creating cutting-edge applications for deep learning and computer vision with PyTorch. Learn and master deep learning with PyTorch in this fun and exciting course with top instructor Rayan Slim. With over 44,000 students, Rayan is a highly trained and experienced instructor who followed a “learn by doing” style to create this incredible course. You will go from being a beginner to an expert in Deep Learning and his instructor will complete each task with you step by step on the screen.
By the end of the course, he will have created cutting-edge deep learning and computer vision applications with PyTorch. The projects built in this course will impress even the most experienced developers and ensure you have practical skills that you can bring to any project or business. This course will teach you to:
Learn to work with the tensor data structure
Deploy Machine and Deep Learning Applications with PyTorch
Build neural networks from scratch
Create complex models with the applied theme of advanced imaging and computer vision
Learn to solve complex computer vision problems using highly sophisticated pre-trained models.
Use style transfer to create sophisticated artificial intelligence applications that can seamlessly recompose images in the style of other images.
PyTorch for Deep Learning and Computer Vision
Learn and master deep learning with PyTorch in this fun and exciting course with top instructor Rayan Slim. With over 44,000 students, Rayan is a highly trained and experienced instructor who followed a “learn by doing” style to create this incredible course. He will go from being a beginner to an expert in Deep Learning and his instructor will complete each task with you step by step on the screen. By the end of the course, he will have created cutting-edge deep learning and computer vision applications with PyTorch. The projects built in this course will impress even the most experienced developers and ensure you have practical skills that you can bring to any project or business. This course will teach you to:
Learn to work with the tensor data structure
Deploy Machine and Deep Learning Applications with PyTorch
Build neural networks from scratch
Create complex models with the applied theme of advanced imaging and computer vision
Learn to solve complex computer vision problems using highly sophisticated pre-trained models.
Use style transfer to create sophisticated artificial intelligence applications that can seamlessly recompose images in the style of other images.