AI Agents

Reinforcement Learning Applicational Benefits

What Is Reinforcement Learning? Before we try to understand machines, let’s explore how humans learn. For any task that we do, we try to optimize the output.

Consider a businessman trying to minimize the cost of producing goods. When he learns that reducing wastage decreases the price, he’ll continuously strive to cut it. Similarly, when he learns that raw-material is available at a cheaper cost, he’ll buy that to minimize cost. This is learning by reinforcement – optimizing the output by learning from it and then adjusting the inputs to optimize the output further. It is a continuous process.

For machines, too, reinforcement learning is applicable. Using output as feedback along with the regular inputs, a continuously improving output can be obtained. Given the speed at which computers operate, a highly-effective solution can be achieved in little time.

Reinforcement learning applicational benefits Businesses stand to benefit immensely using Artificial Intelligence. Most businesses have one major goal – maximize profit. A well-structured data model for profit can use machine learning (ML) to help the business identify the path towards higher profit. Let’s consider an example – A business wants to improve its marketing strategy to generate better revenue. Marketing could consist of many factors like the cost of advertisements, the number of ads, discounts offered, partnering with credit card companies, and so on. A reinforcement-learning based AI can be fed all this data. The machine would try billions of combinations over time to optimize the revenue. This could help identify the metrics that affect income and the optimal range of those metrics to keep revenue growing. This technique works well for a wide range of industries like e-commerce, social networks, offline businesses, medicine, education, among other limitless possibilities.

Superior data science Data science and modeling is the most critical aspect. It’s the superiority of the data science framework that determines how much additional sales a client would get, or how much time a manufacturer would save. We work with a precision-based approach and employ data scientists, statisticians, business analysts, and other experts to work out an effective data model. We use a planned approach to arrive at the best possible solution for the client. Our data science framework consists of these salient steps:

1. Statement of Work
The client’s requirements, also called Statement of Work (SOW) is the base on which a data model is created. Once the client provides its requirements, the experts start working on creating a preliminary model. The team gathers various forms of data and applies multiple sophisticated techniques to arrive at a preliminary data model. This initial model is visualized, analyzed, and refined several times before the team arrives at a model that presents the highest potential on the cost-value proposition. Our focus from the very first stage is to give the best possible benefits to the client. This model undergoes several rounds of revisions and fine-tuning before the experts give the go-ahead for the next step.

2. Milestones
We follow an objective way of reaching the client’s goal. The milestones are Craft, Develop, Deploy, and Evaluate. · Craft: Data is visualized, cleaned, and AI models are created tailored to the client’s requirements. Our experts explore sophisticated deep-learning models if required. After careful inspection of all work done, a report is generated that objectively justifies why a particular model is chosen. This is the first milestone. Upon reaching this, the gates are opened for development. · Develop: Code, software, cloud, and other computing solutions are employed to explore the model based on client-data. Scientists work on refining the model to provide better accuracy. The model is tested extensively, and various sophisticated statistical techniques are employed to see the model’s reaction. · Deploy: We take client-data security very seriously. Depending on the client’s infrastructure and software, state-of-the-art security protocols are used to protect data. The data and the code handling it are handled with extreme care. Once the model is integrated with the client’s system, it is monitored for performance and accuracy. Any specific cases provided by the client are taken care of at this stage. · Evaluate: We continuously monitor the model’s performance and implement rapid changes to keep it efficient and effective. Our experts also explore how the system reacts to new data. We monitor performance in real-time through the cloud. Any changes in the system structure can be tackled, and the model can be advanced. A comprehensive knowledge transfer plan is used to teach the client how to keep the system operating at peak accuracy.

3. Governance
We have a well-defined governance structure to facilitate quality delivery, top-notch security. Our organization follows updated, well-defined IT practices. Here is a sneak peek into our governance structure: · Working Group: This is the client-facing group, our data scientist and others from the group meet the client once, or twice, to understand the requirement and chalk out a way towards profit optimization. · Steering Group: We have a dedicated team of data scientists and machine-learning engineers who work under a dedicated manager. · Escalation Procedures: The client is apprised of all developments during the project. Any unexpected events or accuracy concerns are addressed in the immediate next meeting with the client. Problems related to data are promptly communicated. · Status Reporting: We have regular and robust reporting. The client is kept apprised on the overall status of the project, the milestones, and sub-tasks. We pay special care to include metrics that are required by the executive level – Project name, percent completion, projected completion, issues – regulars, and blockers. Milestone details are also shared comprehensively. · Stakeholder Management: We contact the client POC for any concerns. The stakeholders are well informed and can solve complex issues. · Change Management: We understand the need for change. As per standard IT practices, we have a detailed change request framework that captures and logs the changes as per standard workflow.

4. Data science and the client
Clients have varying requirements and complex data sets. A data model created for one client wouldn’t necessarily work for another. We tailor our data-cleaning and data-engineering approach based on the quality, quantity, and complexity of client data. Due to differences in data, the time needed to complete the data science process varies. We keep our clients informed about these factors and timelines. We have a customized approach to handle the requirements of each client individually. Our four-stage milestone system ensures that our teams deliver the best possible solution tailored specifically to the value the client is seeking. The client is supreme for us. It's our goal to provide our customers with the best possible solution. Data privacy, communication, change, and other processes are state-of-the-art and at par with industry standards. Based on the complexity of the project, we inform our clients of the expected timeline, and it is our constant endeavor to deliver the best in time.

Reinforcement learning has endless potential to solve business problems. We have formulated our solution to cater to varied business requirements. Our solution can be used across the industry for multiple business goals. Our team of data scientists and experts has solved numerous complex problems. Our customers can benefit immensely from this data-driven, AI-based approach to solve business problems. Businesses can make a significant impact on their bottom line by increasing revenue and profits. Our process is meticulously planned and is controlled by a steering group. We take data privacy very seriously – industry standards of enterprise data security are enforced. Our focus is building a strong relationship with the customer and we support our customers for new data, data model revision, and other help that our esteemed clients require.

Are these Features for You?

  • Project Governance, Phases and Milestones with our Statement of Work

  • Full Service Consulting and Code Implementation for Executives

  • For IT Professionals and Leaders continuing the Data Science Methodology

  • Modeling customized to fit to your business data and cost value proposition

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