Category: Model Training & Tuning

Neural Activation Tuning

Neural activation tuning refers to adjusting how individual neurons or groups of neurons respond to different inputs in a neural network. By tuning these activations, researchers and engineers can make the network more sensitive to certain patterns or features, improving its performance on specific tasks. This process helps ensure that the neural network reacts appropriately…

Model Performance Metrics

Model performance metrics are measurements that help us understand how well a machine learning model is working. They show if the model is making correct predictions or mistakes. Different metrics are used depending on the type of problem, such as predicting numbers or categories. These metrics help data scientists compare models and choose the best…

Model Optimization Frameworks

Model optimisation frameworks are tools or libraries that help improve the efficiency and performance of machine learning models. They automate tasks such as reducing model size, speeding up predictions, and lowering hardware requirements. These frameworks make it easier for developers to deploy models on various devices, including smartphones and embedded systems.

Quantum Data Analysis

Quantum data analysis is the process of using quantum computers and algorithms to examine and interpret complex data. Unlike classical computers, quantum systems can process vast amounts of information at once by leveraging quantum bits, which can exist in multiple states simultaneously. This approach has the potential to solve certain data analysis problems much faster…

Model Retraining Pipelines

Model retraining pipelines are automated processes that regularly update machine learning models using new data. These pipelines help ensure that models stay accurate and relevant as conditions change. By automating the steps of collecting data, processing it, training the model, and deploying updates, organisations can keep their AI systems performing well over time.

Quantum State Optimization

Quantum state optimisation refers to the process of finding the best possible configuration or arrangement of a quantum system to achieve a specific goal. This might involve adjusting certain parameters so that the system produces a desired outcome, such as the lowest possible energy state or the most accurate result for a calculation. It is…

Model Performance Tracking

Model performance tracking is the process of monitoring how well a machine learning or statistical model is working over time. It involves collecting and analysing data about the model’s predictions compared to real outcomes. This helps teams understand if the model is accurate, needs updates, or is drifting from its original performance.

Quantum Model Scaling

Quantum model scaling refers to the process of making quantum computing models larger and more powerful by increasing the number of quantum bits, or qubits, and enhancing their capabilities. As these models get bigger, they can solve more complex problems and handle more data. However, scaling up quantum models also brings challenges, such as maintaining…

AI for Forecasting

AI for forecasting uses artificial intelligence techniques to predict future events or trends based on data. It can analyse patterns from large amounts of past information and automatically learn which factors are important. This helps make more accurate predictions for things like sales, weather, or demand without needing manual calculations. Businesses and organisations use AI…