An Introduction to Big Data: NoSQL

An Introduction to Big Data: NoSQL

This semester, I’m taking a graduate course called Introduction to Big Data. It provides a broad introduction to the exploration and management of large datasets being generated and used in the modern world. In an effort to open-source this knowledge to the wider data science community, I will recap the materials I will learn from the class in Medium. Having a solid understanding of the basic concepts, policies, and mechanisms for big data exploration and data mining is crucial if you want to build end-to-end data science projects.

Datacast Episode 11: Psychology and Neuroscience in Data Science with Francisco Carrera Arias

Datacast Episode 11: Psychology and Neuroscience in Data Science with Francisco Carrera Arias

Francisco Carrera Arias, B.S. is currently a data scientist/analyst for MotionPoint Corporation and a research assistant for the Clinical Systems Biology group at Nova Southeastern University. His current work entails performing a variety of data analyses to better inform business decisions as well as using discrete logic to analyze complex biological regulatory networks for the purposes of identifying and simulating treatment courses for chronic illnesses such as Gulf War Illness.

Biologically-Inspired AI: Differential Evolution, Particle Swarm Optimization, and Firefly Algorithms

Biologically-Inspired AI: Differential Evolution, Particle Swarm Optimization, and Firefly Algorithms

There have been significant advances in recent years in the areas of neuroscience, cognitive science, and physiology related to how humans process information. This semester, I’m taking a graduate course called Bio-Inspired Intelligent Systems. It provides broad exposure to the current research in several disciplines that relate to computer science, including computational neuroscience, cognitive science, biology, and evolutionary-inspired computational methods. In an effort to open-source this knowledge to the wider data science community, I will recap the materials I will learn from the class in Medium. Having some knowledge of these models would allow you to develop algorithms that are inspired by nature to solve complex problems.

An Introduction to Big Data: Data Normalization

An Introduction to Big Data: Data Normalization

This semester, I’m taking a graduate course called Introduction to Big Data. It provides a broad introduction to the exploration and management of large datasets being generated and used in the modern world. In an effort to open-source this knowledge to the wider data science community, I will recap the materials I will learn from the class in Medium. Having a solid understanding of the basic concepts, policies, and mechanisms for big data exploration and data mining is crucial if you want to build end-to-end data science projects.

Datacast Episode 10: Linguist turned Data Scientist with Matthias Raess

Datacast Episode 10: Linguist turned Data Scientist with Matthias Raess

Matthias, a linguist turned data scientist, finished his Ph.D. in May 2018 and is currently working as a Manager, Data Analytics at LiveIntent. In his day-to-day, he builds dashboards and models, and runs analyses that drive business decisions and provide stakeholders with meaningful access to data. He enjoys empowering people with data by visualizing and analyzing various types of data visually and/or with statistical and machine learning approaches. He is an avid R/RStudio/RStudio Connect user.

Biologically-Inspired AI: Genetic Algorithms

Biologically-Inspired AI: Genetic Algorithms

There have been significant advances in recent years in the areas of neuroscience, cognitive science, and physiology related to how humans process information. This semester, I’m taking a graduate course called Bio-Inspired Intelligent Systems. It provides broad exposure to the current research in several disciplines that relate to computer science, including computational neuroscience, cognitive science, biology, and evolutionary-inspired computational methods.

Biologically-Inspired AI: Optimization and Local Search

Biologically-Inspired AI: Optimization and Local Search

There have been significant advances in recent years in the areas of neuroscience, cognitive science, and physiology related to how humans process information. This semester, I’m taking a graduate course called Bio-Inspired Intelligent Systems. It provides broad exposure to the current research in several disciplines that relate to computer science, including computational neuroscience, cognitive science, biology, and evolutionary-inspired computational methods.

An Introduction to Big Data: Data Querying

An Introduction to Big Data: Data Querying

This semester, I’m taking a graduate course called Introduction to Big Data. It provides a broad introduction to the exploration and management of large datasets being generated and used in the modern world. In an effort to open-source this knowledge to the wider data science community, I will recap the materials I will learn from the class in Medium. Having a solid understanding of the basic concepts, policies, and mechanisms for big data exploration and data mining is crucial if you want to build end-to-end data science projects.

Datacast Episode 9: Diving into Data Engineering with Mark Sellors

Datacast Episode 9: Diving into Data Engineering with Mark Sellors

Mark Sellors is the Head of Data Engineering at Mango Solutions, a UK based Data Science consultancy. He has more than a decade’s experience working with analytical computing environments, DevOps and Unix/Linux. He uses his experience to help Mango’s customers transform their analytic capabilities to ensure they can make the most of their data.

Datacast Episode 8: From Underwater Communication to Data Science with Chintan Shah

Datacast Episode 8: From Underwater Communication to Data Science with Chintan Shah

Chintan is a data scientist currently working as advanced analytics manager at Avanade. He did his Ph.D. in Underwater Communication where he developed communication systems for commercial applications. He has over 10 years of R&D experience and has worked in academia, oil & gas and consultancy. He is passionate about data science and delivering projects that help companies derive actionable insights.