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With the increasing usage of Social Media such as Twitter and review websites like yelp and rotten tomatoes, it has become important to glean insights from the huge amounts of subjective opinionated data. The Rotten Tomatoes movie review dataset is a corpus of movie reviews used for sentiment analysis, originally collected by Pang and Lee. In their work on sentiment treebanks, Socher et al. used Amazon's Mechanical Turk to create fine-grained labels for all parsed phrases in the corpus. You will get a chance to benchmark your sentiment-analysis ideas on the Rotten Tomatoes dataset. You are asked to label phrases on a scale of five values: negative, somewhat negative, neutral, somewhat positive, positive. Obstacles like sentence negation, sarcasm, terseness, language ambiguity, and many others make this data science project challenging.
In this machine learning project, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.
In this machine learning project, we will predict which coupons a customer will buy.
In this data science project, you will work with German credit dataset using classification techniques like Decision Tree, Neural Networks etc to classify loan applications using R.