Data Science
Cases of Usage Rayi System Provides Services for Data Science
Cases of Usage Rayi System Provides Services for Data Science
Intelligence used operationally
Enhancing process performance through the identification of deviations and undesired trends, the investigation of their underlying causes, and the forecasting and prediction of performance.
Supply chain management
Supply chain management is improved by accurate demand forecasts, suggestions for inventory optimization, and supplier- and risk assessments.
Product Quality
proactive detection of manufacturing process variances that affect product quality and interruptions.
Predictive servicing
Monitoring equipment, spotting and documenting trends that indicate pre-failure and failure stages.
Dynamic route planning
On the examination of vehicle maintenance data, real-time GPS data, route traffic data, road maintenance data, weather data, etc., machine learning algorithms are used to select the best delivery route.
Customization of the customer experience
Customization of the customer experience
Client churn
Creating predictions based on consumer behaviour to find prospective churners.
Optimization of the sales process
Enhanced lead and opportunity scoring, suggestions for the next stage in the sales process, alerts on unfavourable client feedback, etc.
Management of financial risk
Estimating project earnings, identifying financial risks, and determining the creditworthiness of potential clients.
Optimization of patient care
Recognising at-risk patients, providing individualised medical care, foreseeing potential symptom emergence, etc.
Analysis of images
Reducing human mistakes through automated grading, counting, and face or emotional identification.
What We Provide in Data Science Services
1. Analysis of business needs.
Defining the business goals that data science will help to achieve.
Identifying drawbacks of the current data science solution (if any).
Deciding on the deliverables for data science.
2. Data pre-processing.
Data science source determination.
Gathering, transforming, and cleaning data.
3. Developing and designing machine learning (ML) models.
Selecting the best data science methodologies and techniques.
Establishing the standards for the evaluation of future ML model(s).
Development, training, testing, and deployment of ML models.
4. Providing data science results in an agreed format.
Data science insights in the form of reports and dashboards are ready for commercial usage.
Unique ML-driven self-service app (optional).
Integration of ML models into other applications (optional).
Our Cooperation Models
Use of data science solutions
- Simple access to the knowledge or tools needed.
- Constructing a data science solution that meets your specific business objectives and runs successfully.
Consultancy for data science improvement
- Tactical and strategic advice.
- Overcoming issues in a data science project (noisy or filthy data, erroneous projections, etc.).
Constant support and consultation in data science
- Support and development of your data science initiative over time to improve the calibre of insights.
- Adapting the ML models to the environment’s changing needs.
Data science as a service (DSaaS)
- There is no investment in internal data science capabilities.
- Obtaining sophisticated data analytics insights produced by data science technology or improving the data science initiatives already in place.
Technology and Methods We Use
We use advanced machine learning algorithms, such as deep neural networks with 10+ hidden layers, as well as tried-and-true statistical methodologies to uncover the useful insights that your data hides.
Statistics methods
- Descriptive statistics
- ARMA
- ARIMA
- Bayesian inference, etc.
Non-NN machine learning methods
- Algorithms for supervised learning, such as support vector machines, decision trees, and linear and logistic regression.
- Algorithms for unsupervised learning, like hierarchical and K-means clustering.
- Techniques for reinforcement learning, including Q-learning, SARSA, and the temporal differences method.
Deep learning and neural networks
- Recurrent and convolutional neural networks (including LSTM and GRU)
- Autoencoders
- Generative adversarial networks (GANs)
- Deep Q-network (DQN)
- Bayesian deep learning
We Provide Relevant Data Science Services
Consultancy for machine learning
ML-powered solutions are being advised and developed to assist businesses in locating hidden patterns in vast amounts of data to enable accurate forecasting, root-cause analysis, automated visual inspection, etc.
Services for big data
To assist businesses with storing and processing big data in real-time and extracting advanced analytics insights from sizable datasets, big data consultancy, implementation, support, and big data as a service are available.
Services for image analysis
Designing and developing specialised image analysis software.
Mining data services
Obtaining insightful data from huge, diversified, and dynamic data sets without hiring in-house data mining specialists.
Don't Miss the Advantages of Data Science Any More!
Rayi System can support your project with data science best practices if you're prepared to use sophisticated analytical tools like deep learning and machine learning to boost performance and uncover new business prospects.