The TP Group 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 visualization to provide value to our clients. Our data-driven approach to problem-solving allows us to uncover hidden insights and identify opportunities that may not have been apparent otherwise.
Our team is passionate about data science and the potential it has to transform our clients’ businesses.
Data Analysis and Visualization
Uses statistical methods and visualisation tools to uncover patterns, trends, and insights within data.
• tpgroup has experience in developing an Extract, Transform, and Load pipeline to clean, transform and identify relationships within the data to generate a series of robust and insightful dashboards.
• These dashboards drastically reduce the client’s effort involved in analysing the data while improving fidelity and relevance of insights.
• Dashboards provide the user with clear and well-structured reports that provide insight and analysis that can be undertaken automatically and with no user interaction reducing the training burden and increasing productivity.
Involves using machine learning algorithms to build models that can predict future outcomes based on historical data.
• The team works with the clients to define the problem they want to solve through predictive analysis and then prepares the data for analysis, ensuring that it is clean, structured, and suitable for building predictive models
• The team then selecst the most appropriate machine learning algorithm for the problem at hand and trains the predictive model using historical data, validating the model’s accuracy and performance through cross-validation and other techniques.
• Once the predictive model has been trained and validated, the team deploys the model into production, allowing it to be used for making predictions on new data.
Natural Language Processing
Involves using machine learning algorithms to analyse and interpret natural language data, such as text or speech.
- Text Classification: This involves categorising 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): This involves identifying and extracting named entities (such as people, organisations, and locations) from text. Tp Group has experience extracting important information automatically from large volumes of text, such as news articles or social media posts and providing clear actionable insights.
- Sentiment Analysis: This involves analysing text to determine the overall sentiment expressed in the text (e.g. positive, negative, or neutral).
- Topic Modelling: This involves identifying and extracting topics from large volumes of text.