Jose Portilla
Welcome to the best online course for learning about 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 rapidly becoming one of the most popular deep learning frameworks for Python. Deep integration into Python allows popular libraries and packages to be used for easily writing neural network layers in Python. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more.
This course focuses on balancing important theory concepts with practical hands–on exercises and projects that let you learn how to apply the concepts in the course to your own data sets! When you enroll in this course you will get access to carefully laid out notebooks that explain concepts in an easy to understand manner, including both code and explanations side by side. You will also get access to our slides that explain theory through easy to understand visualizations.
In this course we will teach you everything you need to know to get started with Deep Learning with Pytorch, including:
NumPy
Pandas
Machine Learning Theory
Test/Train/Validation Data Splits
Model Evaluation – Regression and Classification Tasks
Instructor Details
Courses : 21
Specification: PyTorch for Deep Learning with Python Bootcamp
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25 reviews for PyTorch for Deep Learning with Python Bootcamp
Add a review
| Price | $19.99 |
|---|---|
| Provider | |
| Duration | 17 hours |
| Year | 2019 |
| Level | All |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
$19.99
Alex Ababei –
Straight to the point. Thank you!
Christoph Pesch –
too long and too many basics for someone who is capable to learn about deep learning.
Bolinyang –
Useful
Sami Elkurdy –
Easy and straightforward installation instructions
Jean Dagenais –
Excellent Instructor!
Jonathan Moatti –
yes
Arash Hamidian –
I like the way Jose teaches ! makes everything easily understandable
Grant Briggs –
Love this course. Excellent coverage of material. Only complaint is that the speed is sometime too fast to code along and required frequent pausing of the video to catch up and fully absorb what is going on. Otherwise, an excellent course!
James Amo –
Easy to follow and the explanation is good
Matthew Higgins –
Instructor spends a bit too much time assuming I’ve never used a PC before. I’m sure this is learned behavior, but it feels excessive.
Hasna Bouazza –
excellent, his explanation is perfect.
Eric Esajian –
I am a big fan of all Jose’s coding courses. Very informative, very knowledgeable, and very easy to understand. Keep the courses coming!
Dibyajyoti Das –
Good in detailed explanation
Peter Edwards –
Jose really breaks things down without overcomplicating it, and is really great (in my experience) compared to other instructors, simply for getting you hands on with Pytorch without getting too heavy and bogged down with all the theoretical aspects. It’s really helped me enjoy the process of getting my toes wet with Pytorch and my experience with Neural Networks
Pavel Konovalov –
As always a great intro to the topic + some intermediate theory cover.
Svein R stad –
This course is exactly what I was looking for! While other courses just loads the MNIST dataset and leaves it at that, this course teaches how to prepare and load your own data of different types. It also teaches early on how to save, load and run your trained models. There is important information here that is missing in a lot of other courses.
Lucas Beerekamp –
It’s a bit shallow. Doesn’t explain much theory. It’s more of a glossary of available methods.
Benjamin Dourthe –
Great course to get more familiar with PyTorch! It’s a great deep learning library, slightly less intuitive than Tensorflow, but with more flexibility to build custom architectures. As all the other courses I have taken from Jose, this one was really well structured and explained. Thanks Jose!
Scott Ferguson –
Jose Portilla is one of my favorite teachers in general. He does an excellent, thorough job of explaining coding principles and their utilities/functions. I only gave 4.5 stars, because I set unattainable 5 star standards.
Anders Albert –
I enjoyed this course very much. It was very practical. Clean, easy to follow examples, along with an exercise per section. I am very familiar with the theory for ANN, CNN, and RNN, so I paid limited attention during the theory lectures. The goal was to get comfortable with PyTorch which was achieved.
Alfonso Tobar –
It started as an interesting course, but towards the end it started to go way too fast, without explaining any details, but dictating the code we needed to run. I think especially in RNNs and NLP chapters there is not a good understanding on the instructor side and adds a lot of chunks without any explanation. It started strong but it ended up being really disappointing.
Debashis Banerjee –
so far its pretty much basic stuffs
Pearl Mary –
The instructor explains everything so clearly.
Teresa Le –
Easy to follow and very interesting to learn
Ikkesh –
Brief review of pandas is very helpful.