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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?
3 projects | reddit.com/r/MachineLearning | 30 Jan 2021
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?
Basic-Algorithms - Basic algorithms and data structures written in different programming languages
python-systemd-tutorial - A tutorial for writing a systemd service in Python
greenberry - A one-line statement language with grammar and infinite look-ahead
C8SALT - A CHIP-8 interpreter written in TI-BASIC.
kuroko - Dialect of Python with explicit variable declaration and block scoping, with a lightweight and easy-to-embed bytecode compiler and interpreter.
stanford-tensorflow-tutorials - This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
PyBasic - Simple interactive BASIC interpreter written in Python
python-minecraft-clone - Source code for each episode of my Minecraft clone in Python YouTube tutorial series.