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Text-mining-and-Analytics-
August 22, 2020 – April 16, 2022
Text mining and analytics for data science
View ProjectLearning-various-classifiers-on-Iris-dataset
June 25, 2020 – February 23, 2022
Performing the model like Decision Tree Page. Coding up KNN from scratch in Python. KNN using SKlearn. Navie Bayes using SKlearn. Boosting in Python. Feature importance using ensemble Classifiers. Voting Classifiers using SKLearn.
View ProjectTwitter-Sentiment-Analysis
June 21, 2020 – March 6, 2022
Investigation of open data from internet-based expressions and opinions could yield fascinating outcomes and bits of knowledge into the universe of popular feelings about any item, administration or identity. The blast of Web 2.0 has prompted expanded action in Podcasting, Blogging, Tagging, Contributing to RSS, Social Bookmarking, and Social Networking. Subsequently there has been a sudden increase of enthusiasm for individuals to mine these tremendous assets of information for suppositions. Sentiment analysis or Opinion Mining is mining of sentiment polarities from online social media. In this project we will talk about a procedure which permits use and understanding of twitter information for sentiment analysis. We perform several steps of text pre-processing, and then experiment with multiple classification mechanisms. Using a dataset of 50000 tweets and TFIDF features, we comparison the accuracy obtained using various classifiers for this task. We find that linear SVMs provide us
View ProjectCultural Fit Analysis
The candidate shows a strong interest in data science through numerous personal projects, indicating self-motivation and a passion for the field. The diversity of projects (from basic Python concepts to advanced deep learning and sentiment analysis) suggests a broad curiosity. However, without information on professional experience or team-based projects, it's difficult to assess collaboration style or alignment with a specific team culture.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's profile primarily lists personal projects without details on team collaboration, problem-solving approaches, or communication in a professional setting.