Data drives Artificial Intelligence, it doesn’t matter if you have big data or only a small amount of data; the results you get are determined by the quality of your data.
The first and most important step in any successful AI project is a thorough examination of the data. This should include rigorous data cleaning and exploratory data analysis (EDA). These steps may need to be repeated several times before moving forward.
Data Cleaning and EDA are time consuming but they significantly increase the chances of successful outcome for your AI project.
Your data may have a story to tell. We can help you gain insights from you data using statistical analysis, machine learning, deep learning and natural language processing.
UFO Software, LLC extensive experience training image classifiers, object detectors and point clouds.
Charles Rice has experience with data science, machine learning, natural language processing, computer vision, SQL and software engineering.
Charles has a Bachelor's degree in Mathematics from Wayne State University in Detroit, Michigan. He studied Computational Intelligence and worked on research projects involving neural networks, reinforcement learning and genetic algorithms at Portland State University.
He has extensive experience working with Python, Pandas, NumPy, spaCy, TensorFlow, Keras, Scikit-Learn, SQL and numerous other data science and machine learning libraries. He has worked on projects for Ford Motor Company, Btrieve, Tektronix, Nike, Xerox and Hewlett-Packard. Charles has worked at several startups often as the technical lead.
As a teenager Charles was involved in the Detroit Electronic Music and Punk Rock scenes. He often built his own effects pedals for his guitar, programmed synthesizers, spent many hours making tape loops and recording music with his friends. He started programming in high school and never stopped.
Currently, he volunteers as the videographer for Chamber Music Camp of Portland