The dataset is from Amazon Review Data (2018) https://nijianmo.github.io/amazon/index.html.
- I here look at Cell Phones and Accessories review dataset for experimentation.
- I have pre-processed this dataset in Jupyter Notebook, please find the code in the Preprocessing Folder
- The script for pre-processing is present here: https://github.com/immanuvelprathap/LSTM-Sentiment-Analysis-AmazonReviews-Dataset/tree/main/Preprocessing
- The CellPhonesRating.csv is too large so i cannot upload it but please follow the pre-processing steps here: https://github.com/immanuvelprathap/LSTM-Sentiment-Analysis-AmazonReviews-Dataset/tree/main/PreprocessingDataset/tree/main/Preprocessing
├── Data
│ ├── CellPhonesRating.csv
│ └── tokenizer.json
├── Images
│ ├── Architecture_LSTM_Model.png
│ ├── The_LSTM_cell.png
│ └── multi_input_and_output_model.png
├── Model
│ ├── LSTM_Model.ipynb
│ └── tf_LSTM_model.h5
├── Preprocessing
│ └── Preprocessing - AmazonReviews Dataset.ipynb
├── README.md
└── gitattributes
import matplotlib as mpl
import matplotlib.pyplot as plt
import os
import re
import shutil
import string
import tensorflow as tf
from tensorflow.keras import regularizers
from tensorflow.keras import layers
from tensorflow.keras import losses
from collections import Counter
import pandas as pd
import numpy as np
import sklearn
from sklearn.model_selection import train_test_split
from sklearn.metrics import classification_report
from tensorflow.keras import preprocessing
from tensorflow.keras.preprocessing.text import Tokenizer
from tensorflow.keras.preprocessing.sequence import pad_sequences
import seaborn as sns
import pydot
[Immanuvel Prathap's Website - Click Here!]