Areas of expertise include:
• Architecting scalable predictive systems that reliably handle multiple data rates, types and sources. Python, Spark, NoSQL, Hadoop
• Combining a variety of data types for superior insight: structured numeric, unstructured text, social media, imagery, sensor telemetry, network protocol/algorithmic, etc. Machine learning, statistics
• Designing explanatory systems that summarize data and justify predictions. Artificial intelligence, causal inference.
At Kwamata we view data mastery as 4 progressive levels:
Kwamata can help take you there.
Kwamata is also exploring several startup concepts while being driven by the Lean Startup methodology. Currently, several minimally viable products (MVPs) are being developed:
Kwame Porter Robinson is a tireless, creative problem solver with a strong background in applied research, machine learning and data science. Prior to starting Kwamata, Kwame has worked on classified projects spanning data science, cyber security and telecommunications research for the Department of Defense. Notably, he was awarded the National Intelligence Meritorious Unit Citation, several challenge coins, and earned his Master’s in Computer Science during that time.He has the ability to work in a variety of computer languages, specializing in Python, is passionate about machine learning and understands distributed processing frameworks and systems.
Kwame has a passion for getting active in the community by mentoring low income high school students in math and science. He recently relocated to Southwest Michigan.
For more details, please refer to his linkedin profile.