Data Science
Experienced data scientists, engineers, and analysts who use their expertise in statistical modelling, machine learning, and data visualization to provide value to our clients.
The TP Group's dedicated data science team has a proven track record of providing data science and analysis services and products within the defence domain. The team has worked on a range of projects, from predictive analytics to Natural Language Processing and visualisation, all with the goal of delivering actionable insights to our clients.
Our team consists of experienced data scientists, engineers, and analysts who use their expertise in statistical modelling, machine learning, and data visualisation to provide value to our clients. Our data-driven approach to problem-solving allows us to uncover hidden insights and opportunities. Our team is passionate about data science and the potential it has to transform our clients’ businesses.
Services
- Data visualisation: Using statistical methods and visualisation tools to uncover patterns, trends, and insights within data
- Data integration: experience in developing an Extract, Transform, and Load pipeline to clean, transform and identify relationships within the data
- Generation of robust and insightful dashboards: reducing effort involved in analysing the data while improving fidelity and relevance of insights.
- Machine learning: using machine learning algorithms to build models that can predict future outcomes based on historical data.
- Data preparation: preparing the data for analysis, ensuring that it is clean, structured, and suitable for building predictive models
- Algorithm selection and training: selection of the most appropriate machine learning algorithm and training the predictive model using historical data, validating the model’s accuracy and performance through cross-validation and other techniques.
- Model deployment: deployment of the model into production, allowing it to be used for making predictions on new data.
- Text Classification: categorisation of text into predefined categories based on the content of the text. For example, to categorise customer feedback into different sentiment categories (e.g. positive, neutral, negative).
- Named Entity Recognition (NER): identification and extraction of named entities (such as people, organisations, and locations) from text. We have considerable experience in extracting important information automatically from large volumes of text, such as news articles or social media posts and providing clear actionable insights.
- Sentiment Analysis: analysis of text to determine the overall sentiment expressed in the text (e.g. positive, negative, or neutral).
- Topic Modelling: identification and extraction of topics from large volumes of text.
Why TP Group?
- More than 30 years' experience in the Defence sector
- Dedicated data science team comprising data scientists, engineers, and analysts
- Constant horizon scanning for emerging technologies in this fast-changing technology sector
- Straightforward to engage through multiple frameworks
- Independent consultancy not affiliated to any software or technology
Our work in Data science
Human entered data by nature will have some errors. This is particularly true when humans are entering large amounts of data under time pressure. This was true for an Army dataset comprising of orders for replacement parts for rotary wing aircraft.
Intelligence Analysts search through an abundance of disparate unstructured reports to identify and extract relevant entities, (people, organisations, equipment, etc.), from which valuable relationships are discovered.