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classification
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- Software Projects
Recommendation System for eLearning contents
In this project eLearning contents are generated by scraping the websites and then keywords are extracted using Spacy library. Clustering techniques are used to cluster the contents as ‘Low’, ‘Medium’ and ‘High’ complexity. The contents are personalized by matching the contents with user’s profile. Cosine Similarity is used to recommend the websites and keywords based on search keywords as entered by the user. Top 10 search results along with the similarity scores will be displayed to the user when the user wants to search a specific eLearning material from the internet.
SKU: Recommendation System for eLearning contents - Software Projects
Telecom Network Anomaly Detection
Network security is becoming increasingly important as large number of applications are running on the top of it. There are number of network parameters that are commonly used to specify the Telecom network. Careful analysis is required to be done in order to understand the vulnerability of the network. Therefore anomaly detection is so important in the network. The data science techniques are used to study the network parameters and then classification algorithms are applied to classify the network issues. The web based application is also developed using Streamlit so that the user can interact with the application by changing the network parameters thereby helping the user to understand whether the network is ‘OK’ or ‘Not OK’.
SKU: n/a - Software Projects
Ground Water Quality Prediction
This project leverages Machine Learning techniques to determine the quality of ground water being considered as drikable. It starts with exploratory data analysis followed by visualizations and classification algorithms such as Logistic Regression, kNN, DecisionTree, Random Forest, XGBoost and so on. The performance of the models are evaluated using confusion metrics and compared to understand their suitability of their usage to solve the business problem.
SKU: n/a
