CloudMoyo – Machine Learning
IDC says the market for Al/ML continues to grow at a rapid pace. Organizations using technologies like machine learning are driving innovation and overall leadership in their respective industries. In a Forbes survey, 6 out 10 organizations cited machine learning and AI as their most significant data initiative in 2019.
Machine learning turns complex situations into intelligent business outcomes by enabling enterprise applications to predict results more accurately. Many experts believe that by 2050, AI/ML technologies will supersede humans in performing all intellectual tasks. The advent of machine learning has transformed businesses, enabling predictive maintenance, quality control, test automation, and more.
CloudMoyo helps businesses leverage our domain expertise in machine learning and AI technologies to build models for analyzing existing and future data streams effectively.
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Here are the top questions businesses ask before they get started with their machine learning initiatives:
- Is my organization ready to adopt and deploy machine learning?
- What is needed to start the machine learning initiatives?
- How is machine learning relevant to our business? What are the use cases?
- What is the business case for machine learning? How to accelerate ROI?
CloudMoyo Machine Learning JumpStart Program
Predictable, packaged, and high-impact engagement program to jumpstart ML initiatives within your organization
CloudMoyo ML JumpStart Program is a 4-week engagement that will enable organizations to assess their enterprise readiness for the application of ML algorithms. The program is designed to help CIOs of medium-sized companies to understand data relevancy and organizational readiness, and the business outcome will be recommendations for ML use cases for machine learning technologies given the availability of applicable data sets within the organization.
Understand business imperatives and assess relevant ML applications through stakeholder meetings, interviews, and questionnaires, as well as identification of pain-points.
Collect sample data sets, evaluate and prepare data. Plan for data sets required for the ML algorithms as well as conduct test runs to evaluate applicability.
Build the Proof of Concept, train the model to identify patterns and anomalies, make model enhancements, and measure relevant metrics.
Deliver comprehensive, customized reports with recommendations for data architecture required for enabling ML use cases.
Our customers benefit from both normative and predictive analysis that improves business decisions and drives transformative business results.
Prediction and prescription
Use AI and ML to make predictions about future trends and prescribe actions
Identify places, logos, people, objects and several other variables in an image or a video
Suggest products or services based on items such as past purchases, demographics, and search history
Identify and catalog a piece of text according to the tone conveyed by it
Internet of Things
Identify patterns and anomalies in sensor data to avoid accidents and eliminate or reduce equipment downtime
Robotic process automation (RPA)
Mimic and integrate human actions within digital systems to optimize business processes
Natural Language Processing (NLP)
Parse existing text data to identify patterns, risks, and new business opportunities