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word-tokenization

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Sumegha22 / Coronavirus-Tweet-Sentiment-Analysis-Classification-ML-Project

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Sentiment analysis on tweets related to the coronavirus (COVID-19) can be useful for understanding public opinion, tracking trends, and identifying potential areas of concern. In this task, we can use machine learning techniques, such as logistic regression or support vector machines, to predict the sentiment of a given tweet as positive, negative,

python nlp machine-learning word sklearn eda naive-bayes-classifier logistic-regression confusion-matrix decision-tree-classifier stochastic-gradient-descent bags-of-words word-tokenization
  • Updated Apr 21, 2023
  • Jupyter Notebook

Rachakondaganesh / Using-NLP-Online-and-Retail-Order-Review-Project

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analyzed customer reviews from online and retail orders. Performed sentiment analysis, keyword extraction, and topic modeling to identify trends, satisfaction drivers, and pain points. Used Python (NLTK, spaCy) and visualization tools to present actionable insights for improving customer experience and product strategy.

lambda pandas stopwords unicode-data nlp-machine-learning stemming bivariate-analysis matplotlib-pyplot univariate-analysis sent-tokenize word-tokenization trivariate-analysis
  • Updated Oct 8, 2025
  • Python

wanyingng / CS50ai

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Harvard University CS50’s Introduction to Artificial Intelligence with Python (2025)

first-order-logic pagerank-algorithm q-learning bayesian-network propositional-logic alpha-beta-pruning convolutional-neural-network context-free-grammar backtracking-search markov-chain-monte-carlo minimax-algorithm probability-theory maintaining-arc-consistency ac3-algorithm inference-logic breadth-first-search-algorithm word-tokenization masked-language-model nearest-neighbor-classification epsilon-greedy-algorithm
  • Updated Oct 29, 2025
  • Python

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