pkmital/tensorflow_tutorials
TensorFlow tutorial collection covering fundamentals through neural network architectures like autoencoders, convnets, and residual networks.
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This repository contains a collection of Jupyter notebooks and Python source code teaching TensorFlow from basics to intermediate applications. Topics covered include linear and polynomial regression, logistic regression, convolutional neural networks with batch normalization, deep autoencoders (standard, denoising, convolutional, and variational), and residual networks. The tutorials include pre-compiled wheels for GPU-enabled setup on Ubuntu with CUDA support.
Frequently asked
- What is pkmital/tensorflow_tutorials?
- TensorFlow tutorial collection covering fundamentals through neural network architectures like autoencoders, convnets, and residual networks.
- Is tensorflow_tutorials open source?
- Yes — pkmital/tensorflow_tutorials is an open-source project tracked on heatdrop.
- What language is tensorflow_tutorials written in?
- pkmital/tensorflow_tutorials is primarily written in Jupyter Notebook.
- How popular is tensorflow_tutorials?
- pkmital/tensorflow_tutorials has 5.7k stars on GitHub.
- Where can I find tensorflow_tutorials?
- pkmital/tensorflow_tutorials is on GitHub at https://github.com/pkmital/tensorflow_tutorials.