mirror of
https://github.com/gmihaila/ml_things.git
synced 2021-10-04 01:29:04 +03:00
154697f287b6d07cd7f9a8fda4ccccde99c0b186
Machine Learning Toolkit
Here is a list of notebooks written in Google Colab of Machine Learning models using toy examples.
Main libraries used: Tensorflow, Keras, CatBoost,
Each notebooks:
-
has brief description of the model and implementation.
-
can be run in Google Colab.
-
is using toy data for educational purposes
Notebook:
-
Cat Boost implementation.
-
Check GPU in Tensorflow.
-
Cuda Setup guide.
-
Keras Checkpoints to do callbacks when training large Deep Learning models.
-
Keras embedding layer How it works and how to add it to your Deep Learning Model.
-
Keras Generator use when dealing with Big Data. How to plug it to a Deep Learning model.
-
Keras Time Distribution Explanation oh how it works and when to use it.
-
Keras Tokenizer Example of how to use it and fix the bug.
-
Sequesnce To Sequence model. Implementation for translation.
-
Text Summarization Prototype using Sequence To Sequence architecture with actual data.
-
Neural Network Keras vanila implementation. Toy example with actual data.
-
Word Embedding How to load and plot using PCA.
-
-
-
Description
No description provided
google-colabmachine-learningnlpnlp-machine-learningnotebookspython-snippetspytorchsnippetstransformer
Readme
Apache-2.0
69 MiB
Languages
Jupyter Notebook
99.5%
Python
0.5%