Modern Graph Theory Algorithms with Python
Harness the power of graph algorithms and real-world network applications using Python
Colleen M. Farrelly & Franck Kalala Mutombo
Modern Graph Theory Algorithms with Python
Harness the power of graph algorithms and real-world network applications using Python
Colleen M. Farrelly & Franck Kalala Mutombo
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Colleen M. Farrelly is a lead data scientist and researcher with a broad industry background in machine learning algorithms and domains of application. While her focus has been industry, she also publishes academically in geometry, network science, and natural language processing. Colleen earned a graduate degree in Biostatistics from the University of Miami. Her work history includes fields like nuclear engineering, public health, biotechnology, retail, educational technology, and human behavior analytics. She previously published The Shape of Data, a comprehensive overview of machine learning from a geometric perspective. Colleen is currently focused on applications of generative models and tech education in the developing world Franck Kalala Mutombo is a Professor of Mathematics at Lubumbashi University and former Academic Director of AIMS-Senegal. He previously worked in a research position at Strathclyde University and at AIMS-South Africa in a joint appointment with the University of Cape Town. He holds a PhD in Mathematical Sciences (with focus in network science) from the University of Strathclyde, Glasgow, Scotland. His current research considers the impact of network structure on long-range interactions applied to epidemics, diffusion, object clustering, differential geometry of manifolds, finite element methods for PDEs, and data science. Currently, he teaches at University of Lubumbashi and across the AIMS Network.
Colleen M. Farrelly is a lead data scientist and researcher with a broad industry background in machine learning algorithms and domains of application. While her focus has been industry, she also publishes academically in geometry, network science, and natural language processing. Colleen earned a graduate degree in Biostatistics from the University of Miami. Her work history includes fields like nuclear engineering, public health, biotechnology, retail, educational technology, and human behavior analytics. She previously published The Shape of Data, a comprehensive overview of machine learning from a geometric perspective. Colleen is currently focused on applications of generative models and tech education in the developing world Franck Kalala Mutombo is a Professor of Mathematics at Lubumbashi University and former Academic Director of AIMS-Senegal. He previously worked in a research position at Strathclyde University and at AIMS-South Africa in a joint appointment with the University of Cape Town. He holds a PhD in Mathematical Sciences (with focus in network science) from the University of Strathclyde, Glasgow, Scotland. His current research considers the impact of network structure on long-range interactions applied to epidemics, diffusion, object clustering, differential geometry of manifolds, finite element methods for PDEs, and data science. Currently, he teaches at University of Lubumbashi and across the AIMS Network.
Colleen M. Farrelly is a lead data scientist and researcher with a broad industry background in machine learning algorithms and domains of application. While her focus has been industry, she also publishes academically in geometry, network science, and natural language processing. Colleen earned a graduate degree in Biostatistics from the University of Miami. Her work history includes fields like nuclear engineering, public health, biotechnology, retail, educational technology, and human behavior analytics. She previously published The Shape of Data, a comprehensive overview of machine learning from a geometric perspective. Colleen is currently focused on applications of generative models and tech education in the developing world Franck Kalala Mutombo is a Professor of Mathematics at Lubumbashi University and former Academic Director of AIMS-Senegal. He previously worked in a research position at Strathclyde University and at AIMS-South Africa in a joint appointment with the University of Cape Town. He holds a PhD in Mathematical Sciences (with focus in network science) from the University of Strathclyde, Glasgow, Scotland. His current research considers the impact of network structure on long-range interactions applied to epidemics, diffusion, object clustering, differential geometry of manifolds, finite element methods for PDEs, and data science. Currently, he teaches at University of Lubumbashi and across the AIMS Network.