Data science services assist businesses in conducting tests on their data in quest of commercial insights. To suit our clients’ most specific analytics needs, Primoris Systems offers data science consulting services utilising machine learning, artificial intelligence, and deep learning technologies.
Use Cases Primoris Systems Offers Data Science Services
What We Offer in Data Science Services
1. Business needs evaluation
- Defining the business goals that data science will help to achieve
- Identifying drawbacks of the current data science solution
- Deciding on the deliverables for data science
2. Data preparation
- Data science source determination
- Gathering, transforming, and cleaning data
3. ML model evaluation and tuning
4. Design and development of machine learning (ML) models
- Data science insights in the form of reports and dashboards are ready for commercial usage.
- Self-service app powered by custom ML (optional).
- Integration of ML models into other applications is optional.
5. Data science support consultations, user and administrator training
Models of Collaboration We Provide
Use of data science solutions
- Simple access to the knowledge or tools needed
- Constructing a data science solution that meets your specific company 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.)
Ongoing Advice and Assistance in Data Science
- Support and development of your data science effort throughout 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 projects already in place.
Technologies and Methods, We Employ
We use sophisticated 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 conceals. Methods we use are as:
- Statistically descriptive
- ARIMA ARMA
- Bayesian analysis, etc.
Machine learning techniques Non-NN
- Algorithms for supervised learning, such as support vector machines, decision trees, and linear and logistic regression
- Algorithms for unsupervised learning, such hierarchical and K-means clustering
- Techniques for reinforcement learning, including Q-learning, SARSA, and the temporal differences approach
Deep Learning and Neural Networks
- Recurrent and convolutional neural networks, including LSTM and GRU Autoencoders
- GANs, or generative adversarial networks
- DQN, or Deep Q Network
- Deep Bayesian learning
We Provide Related Data Science Services
ML-powered solutions are advised and developed to assist businesses in locating hidden patterns in vast amounts of data to allow accurate forecasting, root-cause analysis, automated visual inspection, etc
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
The creation of specialised image analysis software
Obtaining insightful data from vast, diverse, and dynamic data sets without hiring in-house data mining specialists