Packt Publishing
PyTorch: written in Python, is grabbing the attention of all data science professionals due to its ease of use over other libraries and its use of dynamic computation graphs.
PyTorch is a Deep Learning framework that is a boon for researchers and data scientists. It supports Graphic Processing Units and is a platform that provides maximum flexibility and speed. With PyTorch, you can dynamically build neural networks and easily perform advanced Artificial Intelligence tasks.
This comprehensive 2–in–1 course takes a practical approach and is filled with real–world examples to help you create your own application using PyTorch! Begin with exploring PyTorch and the impact it has made on Deep Learning. Design and implement powerful neural networks to solve some impressive problems in a step–by–step manner. Build a Convolutional Neural Network (CNN) for image recognition. Also, predict share prices with Recurrent Neural Network and Long Short–Term Memory Network (LSTM). You’ll learn how to detect credit card fraud with autoencoders and much more!
By the end of the course, you’ll conquer the world of PyTorch to build useful and effective Deep Learning models with the PyTorch Deep Learning framework with the help of real–world examples!
Contents and Overview
This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.
Instructor Details
Courses : 212
Specification: PyTorch: Deep Learning with PyTorch – Masterclass!: 2-in-1
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15 reviews for PyTorch: Deep Learning with PyTorch – Masterclass!: 2-in-1
Add a review
| Price | $14.99 |
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| Provider | |
| Duration | 7.5 hours |
| Year | 2018 |
| Level | Beginner |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
$14.99
Mark McQuade –
Great course, learning a lot, highly recommend it!
Bryce Asay –
I want to like this course but I am really frustrated. When we get to the first neural network example he goes through without explaining how to get the data set, he used custom methods and tells us to figure it out. Part of the reason I am taking this course is to learn how to use Pytorch by an instructor, not to just figure it out. Additionally, there is no way to contact the instructor since it was published by a third party. If I get a response I am happy to change my review since I really want to like it and I hate to have the semantics get in the way of a good course.
Bryce Asay –
I want to like this course but I am really frustrated. When we get to the first neural network example he goes through without explaining how to get the data set, he used custom methods and tells us to figure it out. Part of the reason I am taking this course is to learn how to use Pytorch by an instructor, not to just figure it out. Additionally, there is no way to contact the instructor since it was published by a third party. If I get a response I am happy to change my review since I really want to like it and I hate to have the semantics get in the way of a good course.
Marzieh Mehdizadeh –
It is great, but needs more detail explanations.
Marzieh Mehdizadeh –
It is great, but needs more detail explanations.
Stephan H hne –
Deutlichkeit der Aussprache k nnte besser sein. Am Ende waren die Folien unscharf.
Stephan H hne –
Deutlichkeit der Aussprache k nnte besser sein. Am Ende waren die Folien unscharf.
L o Boisvert –
Very good class if you already know machine learning/deep learning fundamentals
L o Boisvert –
Very good class if you already know machine learning/deep learning fundamentals
Ahmed N Alkanaq –
One star for covering the basic principles, no stars for the horrible accent; one star for using different examples for demonstration; minus two stars for using messed up English like Happens to be a truck!!
Ahmed N Alkanaq –
One star for covering the basic principles, no stars for the horrible accent; one star for using different examples for demonstration; minus two stars for using messed up English like Happens to be a truck!!
Florent Guinier –
A lot of material and various concept are well explained. However the course have close to 0 practical exercice witch is a problem. Also video quality could be improved some video are not very usefull and some overs goes too fast. This course is thus a good match if you want to gain an overview on pytorch and the presented ML concept, however you will need to take a more detailed one if you really want to apply this knowledge.
Florent Guinier –
A lot of material and various concept are well explained. However the course have close to 0 practical exercice witch is a problem. Also video quality could be improved some video are not very usefull and some overs goes too fast. This course is thus a good match if you want to gain an overview on pytorch and the presented ML concept, however you will need to take a more detailed one if you really want to apply this knowledge.
Devansh Zurale –
I’d like to have some quizzes or homeworks to try myself so I get a better hang of the material. I’m very impressed with the flow of the course.
Yassine Barhoumi –
at the end of the course it feels like the course is wrapping up to fast, as it feels like a task that need to end, and that affected the detailed explanation that we saw in the beginning of the second part.