Write some Software

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tweets from streaming api, to MongoDB database, apply feature extraction (BOF, TF-IDF or other), and classfying the tweets using Machine Learning Model(SVM, Naive Bayes and Entropy) Relevant Skills and Experience Python Machine Learning Twitter web services - rest and streaming Sentinment analysis NLP Database - SQL, Postgresql, Mongodb Proposed Milestones £122 GBP - final

# Sentiment Analysis Hi - I have done sentiment project and aware of Twitter API (streaming & search). I am familiar with Naive Bayes Machine learning algorithm for text classification. Relevant Skills and Experience Python, Data Science, Node.JS, MongoDB Twitter API Machine learning algorithm - Naive Bayes NLP techniques - BOF, TF-IDF Proposed Milestones £50 GBP - Setup server £150 GBP - Start pulling tweets and storing them in MongoDB £100 GBP - Apply NLP techniques and feature extraction £100 GBP - Apply text classification algorithm to calculate sentiments Looking forward for your reply. thank you.

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1. Twitter API to grab data 2. Clean and store it in MongoDB as Json 3. Run a ML algorithm classify the positive and negative sentiments 4. Store the values again mongoDB Relevant Skills and Experience Python, MongoDB, ML, Scraping Proposed Milestones £222 GBP - Twitter api, Mongo DB storage, ML Model building, Demo

Good knowledge on Twitter APIs as well as Machine Learning algorithms Relevant Skills and Experience R, Twitter API, Good conceptual knowledge in Text Analytics Proposed Milestones £50 GBP - Start of the engagement £140 GBP - Delivery of the Code £32 GBP - User Acceptance and bug fixes (if any) Would like to share a set of questions once it is awarded to me