Hands-On-Deep-Learning-Algorithms-with-Python
Hands-On Deep Learning Algorithms with Python, By Packt (by PacktPublishing)
PyTorchZeroToAll
Simple PyTorch Tutorials Zero to ALL! (by hunkim)
| Hands-On-Deep-Learning-Algorithms-with-Python | PyTorchZeroToAll | |
|---|---|---|
| 1 | 1 | |
| 107 | 3,825 | |
| 3.7% | - | |
| 0.0 | 0.0 | |
| over 1 year ago | almost 2 years ago | |
| Jupyter Notebook | Python | |
| MIT License | - |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Hands-On-Deep-Learning-Algorithms-with-Python
Posts with mentions or reviews of Hands-On-Deep-Learning-Algorithms-with-Python.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-01-30.
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[D] I'm trying to do more stuff in pure Tensorflow. Is there an in-depth book that explain constructing recurrent, convolutional, graph etc layers in it?
The code : https://github.com/PacktPublishing/Hands-On-Deep-Learning-Algorithms-with-Python
PyTorchZeroToAll
Posts with mentions or reviews of PyTorchZeroToAll.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-01-30.
-
[D] I'm trying to do more stuff in pure Tensorflow. Is there an in-depth book that explain constructing recurrent, convolutional, graph etc layers in it?
I'm doing this rn, but with PyTorch. I look for notebooks/scripts (https://github.com/hunkim/PyTorchZeroToAll, primarily) on github read and copy them, along with the deeplearning book. Surprisingly pretty much everything just clicks now, it's my third attempt reading the text though. I don't think any book serves the purpose well, except for knowing the well established conventions of the field.
What are some alternatives?
When comparing Hands-On-Deep-Learning-Algorithms-with-Python and PyTorchZeroToAll you can also consider the following projects:
fastbook - The fastai book, published as Jupyter Notebooks
python-systemd-tutorial - A tutorial for writing a systemd service in Python
comet-examples - Examples of Machine Learning code using Comet.ml
python-minecraft-clone - Source code for each episode of my Minecraft clone in Python YouTube tutorial series.
Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.
vision_transformer - Discover how to build vision transformer from scratch with this comprehensive tutorial. Follow our step-by-step guide to create your own vision transformer.
stanford-tensorflow-tutorials - This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
Hands-On-Deep-Learning-Algorithms-with-Python vs fastbook
PyTorchZeroToAll vs python-systemd-tutorial
Hands-On-Deep-Learning-Algorithms-with-Python vs comet-examples
PyTorchZeroToAll vs python-minecraft-clone
Hands-On-Deep-Learning-Algorithms-with-Python vs Made-With-ML
PyTorchZeroToAll vs vision_transformer
Hands-On-Deep-Learning-Algorithms-with-Python vs stanford-tensorflow-tutorials
PyTorchZeroToAll vs stanford-tensorflow-tutorials