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From the Kindle Store Reviews on Amazon, sentiment analysis and book recommendation. Used Keras, FastText from Torch, and BERT. For recommender systems; SVDS, cosine-similarity, and solved the cold…
PCA TSNE, Text preprocessing, EDA, Amazon food review dataset
Cleaning Text features using Text feature techniques and NLP(Bag Of Words, Tf-idf, Word2Vec etc) on Amazon Fine Food Reviews Dataset.
Data cleaning, Text preprocessing and TSNE visualisation on Amazon Food Reviews dataset
Utilities for preprocessing text for deep learning with Keras
Sentiment Analysis on Movie Review using Bing Liu's Dictionary, Python, Meaningcloud
A PyTorch CNN for classifying the sentiment of movie reviews, based on the paper "Convolutional Neural Networks for Sentence Classification" by Yoon Kim (2014).
A seq2seq model that can generate summaries from fine food reviews on Amazon.
Text preprocessing tools in python.
IMDB Movie Reviews - Text preprocessing and classification. Includes BOW model, TF_IDF, VADER entiment analysis, Topic Modelling using Latent Dirichlet Allocation and Word Embeddings. (Python)
Text preprocessing by removing stop words, URLs and Numbers which will not give much meaning to sentence. Creating a Feature Vector for each word in the Review by taking the word meaning from dicti…
Data scraping, preprocessing , pos tagging, stemming and lemmatization, tfidf calculation, sentiment analysis , topic modeling on review texts to perform brand comparison
Explaining textual analysis tools in Python. Including Preprocessing, Skip Gram (word2vec), and Topic Modelling.
Starter code to solve real world text data problems. Includes: Gensim Word2Vec, phrase embeddings, Text Classification with Logistic Regression, word count with pyspark, simple text preprocessing, …
[Machine Learning | Data Analysis] Data Analysis on Amazon Fine Food Reviews dataset.
Machine learning algorithm such as KNN,Naive Bayes,Logistic Regression,SVM,Decision Trees,Random Forest,k means and Truncated SVD on amazon fine food review
Amazon Fine Food Reviews Sentiment Analysis with Recurrent Neural Network
Extracts apparel details from amazon api and recommends similar products using nltk and keras
Different recommendation methods for books: 1) content-based with Amazon API 2) Low-rank matrices decomposition 3) Clustering of similar items
Tutorial for Sentiment Analysis using Doc2Vec in gensim (or "getting 87% accuracy in sentiment analysis in under 100 lines of code")
Text Pre-Processing
Text pre-processing library for deep learning (Keras, tensorflow).
We used Machine learning techniques to evaluate past data pertaining to the stock market and world affairs of the corresponding time period, in order to make predictions in stock trends. We built a…
project4-team-2 created by Classroom for GitHub
Sentiment Analysis For Movie Reviews And Recommendation System From Reviews