In this step, our team collaborates with you to either create a brand-new machine learning model or choose a pre-existing model that suits your project requirements. We take care of implementing the model using a programming language such as Python.

To prepare your data for training the machine learning model, we undertake the process of data labeling. This involves assigning a specific class or label to each individual piece of data in your dataset.

In this step, our team collaborates with you to either create a brand-new machine learning model or choose a pre-existing model that suits your project requirements. We take care of implementing the model using a programming language such as Python.

Then, we collaborate with you to refine the training process and explore various techniques aimed at enhancing the model's accuracy. This may involve adjusting the model's hyperparameters or utilizing different data preprocessing techniques.

Once the model satisfies your performance criteria, our team deploys it to a production environment. This involves integrating the model into an existing application or developing a new application specifically designed to leverage the model's capabilities.