Social graph data mining
Social graphs are maps of relationships between connections, in which clusters of names (nodes) and connections (edges) illustrate who’s connected to whom. Assuming someone is connected with people from different parts of his or her life, the graph will likely bear this out visually via, for example, distinct clusters of professional, personal and business connections.
Me concernant
We are a professional team focusing on machine learning R&D and AI applications including image/video data, text/natural language data and business data analysis: # Machine Learning and pattern recognition: Neural networks and deep learning (e.g. CNN, R-CNN, Fast R-CNN, ResNet) Clustering (e.g. automatic hierarchical clustering) Classification (e.g. SVM, decision trees, Bayes classifier) Regression (e.g. linear/nonlinear regression) Reinforcement learning (e.g. brute force, value function) # Image/video data mining: Image feature extraction/segmentation Object detection Object tracking Motion recognition # Text mining/language data mining: Web data scraping/site crawling Text categorization Semantic analysis # General data analytics: Business/Industrial big data analysis Data visualization and analysis # Mathematics: Optimization Mathematics modelling
$35 $ US / h
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