https://github.com/camara94/natural-language-processing-tensorflow
Natural Language processing in tensorflow
https://github.com/camara94/natural-language-processing-tensorflow
dataset deep-learning lstm-neural-networks lstm-sentiment-analysis machine-learning natural-language-processing nlp nlp-keywords-extraction nlp-machine-learning rnn rnn-tensorflow sentiment-analysis tensorflow text-classification
Last synced: 8 months ago
JSON representation
Natural Language processing in tensorflow
- Host: GitHub
- URL: https://github.com/camara94/natural-language-processing-tensorflow
- Owner: camara94
- License: mit
- Created: 2022-04-03T23:38:27.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2022-04-11T06:38:37.000Z (about 4 years ago)
- Last Synced: 2025-03-21T13:45:18.641Z (over 1 year ago)
- Topics: dataset, deep-learning, lstm-neural-networks, lstm-sentiment-analysis, machine-learning, natural-language-processing, nlp, nlp-keywords-extraction, nlp-machine-learning, rnn, rnn-tensorflow, sentiment-analysis, tensorflow, text-classification
- Language: Jupyter Notebook
- Homepage:
- Size: 28.8 MB
- Stars: 10
- Watchers: 2
- Forks: 7
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# natural-language-processing-tensorflow
Natural Language processing in tensorflow
## Word Encoding
## Same With ASCI CODE
With asci analysis the word **LISTEN** and *SILENT** are the same value but the two words are very differents of meaning.
## How Sentiment Analysis Work
* How we can observed the similarity between two words
* Now if we look at the two sentences to determine the difference between two sentences.
## How To Analyse The Synthaxe
## Creating The List Of Sequences
## Complete Analysis Corpus
## Padding Sequences
## Result Of Padding Sequence
## Personnalize Padding
## Sarcasm in News Headlines Dataset by Rishabh Misra
[https://rishabhmisra.github.io/publications/](https://rishabhmisra.github.io/publications/)
## How To Load Sarcasm Dataset
## How To Analysis Sarcasm Dataset
## Sarcasm Detection
* [https://www.kaggle.com/datasets/rmisra/news-headlines-dataset-for-sarcasm-detection](https://www.kaggle.com/datasets/rmisra/news-headlines-dataset-for-sarcasm-detection)
## Build-in Dataset In Tensorflow
## Dataset
## Verify Tensorflow Version
## Import Tensorflow Dataset
## Split data
## Tokenizer
## Model
OR
## Training Model
## Expect Layer
## Reverse Word Index
## Vecteor In Embedded Data
## Download In Colab
## Model For Sarcasm Dataset
### Importation of Tokenizer And Pad_sequence
### Hyper Parameters
### Download Sarcasm Dataset
### Loading Sarcasm Dataset
### Building a classifier for the sarcasm dataset
### Sequence Dataset
### Create A Model
### Summarization Of Model
### Training The Model
### Plotting The Result Of Training
## TensorFlow datasets
* [https://github.com/tensorflow/datasets/tree/master/docs/catalog](https://github.com/tensorflow/datasets/tree/master/docs/catalog)
* [https://www.tensorflow.org/datasets/catalog/overview](https://www.tensorflow.org/datasets/catalog/overview)
## Subwords text encoder
* [https://www.tensorflow.org/datasets/api_docs/python/tfds/deprecated/text/SubwordTextEncoder](https://www.tensorflow.org/datasets/api_docs/python/tfds/deprecated/text/SubwordTextEncoder)
## Diving into the code: Encode And Decode
## Classify Sub Word
## RNN
The neural Network is kind a function that we can a data and label it give a rules
## How RNN Work
## Visualize A Sequence
## More About RNN
* [https://www.coursera.org/lecture/nlp-sequence-models/deep-rnns-ehs0S](https://www.coursera.org/lecture/nlp-sequence-models/deep-rnns-ehs0S)
## How To Understang The Context Of Word
## Uni Directional Cell State
## Bi Directional Cell State
## How To Implement LSTM in Tensorflow
## How To Stack LSTM
## More About LSTMs
* [https://www.coursera.org/lecture/nlp-sequence-models/long-short-term-memory-lstm-KXoay](https://www.coursera.org/lecture/nlp-sequence-models/long-short-term-memory-lstm-KXoay)
## Generation A New Text Process
### Preparing the training data
### More on the training data
### Finding what the next word should be
### Example of Text Generated
### Use Bidirectional LSTM
### Example After Training With Bidirectional LSTM
### Predicting a word
* Tokenize the word to predicting
* Padded A Sequence
* Passed To Model For Prediction
* Reverse Look out
* Generation By Doing Ten Time
* Result
### Download A Corpus
### Looking into the code
## Userful Link
* [https://www.tensorflow.org/api_docs/python/tf/keras/preprocessing/text/Tokenizer](https://www.tensorflow.org/api_docs/python/tf/keras/preprocessing/text/Tokenizer)
* [https://ai.stanford.edu/~amaas/data/sentiment/](https://ai.stanford.edu/~amaas/data/sentiment/)
* [https://github.com/tensorflow/datasets/tree/master/docs/catalog](https://github.com/tensorflow/datasets/tree/master/docs/catalog)
* [https://www.tensorflow.org/datasets/catalog/overview](https://www.tensorflow.org/datasets/catalog/overview)
* [https://www.tensorflow.org/text/tutorials/text_generation](https://www.tensorflow.org/text/tutorials/text_generation)