Retaining the human in the algorithms, Machine Learning strives to simulate human intelligence.

OperationIT has the Technical Talent that can create new combinations of technology, human skills, data, and cognitive computing to create artificial intelligence as an aid to human endeavor.

OperationIT’s AI Talent pool use machine learning tools and algorithms to help companies develop AI-driven products and solutions. They have profound knowledge and experience in designing, implementing and integrating Artificial Intelligence solutions within the client’s business environment.

Our Cognitive and Deep Learning team have expertise in leading the application prototyping and development for on premise cognitive search and analytics technologies. They have experience with AI, machine learning, cognitive computing, text analytics, natural language processing, analytics and search technologies, vendors, platforms, APIs, microservices, enterprise architecture and security architecture.

Not only do they have the underlying GPU programming and parallel processing skills using C/C++, Java, Scala, MATLAB, or Python, they have the business experience in strategic product development, product innovation and strategy efforts. They have experience evaluating market and technology trends, key providers, legal/regulatory climate, product positioning, and pricing philosophy.

In addition, they have the skills and capabilities to

  • Work with large-scale data sets, collect, process and cleanse raw data from a wide variety of sources.
  • Transform and convert unstructured data set into structured data products. Identify, generate, and select modeling features from various data set.
  • Train and build machine learning models to meet product goals.
  • Innovate new machine learning techniques to address product and business needs.
  • Analyze and evaluate performance results from model execution.

OperationIT has access to and can provide you with AI and Data Science expertise that have strong background and experience in machine learning and information retrieval. They have experience managing end-to-end machine learning pipeline from data exploration, feature engineering, model building, performance evaluation, and online testing with TB to Petabyte-size datasets.

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