Data Science is an interdisciplinary field that involves the use of statistical and computational methods to extract insights and knowledge from data. It combines aspects of statistics, mathematics, computer science, and domain-specific knowledge to process, analyze, and interpret data to solve real-world problems.
Data Science Services
Data science services include data science consulting, development, and support to enable companies to run experiments on their data in search of business insights.
Total Data Strategy
Our complete data strategy encourages a culture of data-driven decision-making, resulting in the greatest possible business effect. We strengthen your existing data activities while also uncovering new use cases and making recommendations in collaboration with our team of Data Scientists.
Consulting services for Data Science and Artificial Intelligence (AI)
We use AI computations and data mining techniques to create data structures and information architecture that are diverse, resilient, and scalable for your company needs. Our approaches enable the development of AI pipelines in programming and online applications.
Data Science Technologies
Methods We Use
- Descriptive statistics
- Bayesian inference, etc.
- Decision trees, linear regression, logistic regression, and support vector machines are examples of supervised learning algorithms.
- Unsupervised learning methods such as K-means clustering and hierarchical clustering are examples of unsupervised learning algorithms.
- Q-learning, SARSA, and temporal differences approaches are examples of reinforcement learning methods.
- Recurrent and convolutional neural networks (including LSTM and GRU)
- Adversarial networks that generate (GANs)
- Q-network in depth (DQN)
- Deep Bayesian learning