Hire Data Scientists

Our data scientists collect structured and unstructured data using web scraping and API integration and prepare them using techniques like feature engineering and data normalization to ensure the data is ready for model training.

Our data scientists leverage techniques like EDA, experimentation, and hypothesis testing to select the ideal ML algorithm for your project. They also use methods like Grid search and Bayesian optimization for hyperparameter tuning to ensure there are no inefficiencies in the model being developed.

Once deployed, our data scientists use evaluation metrics like precision, accuracy, recall and F1 score to resolve any anomalies in the model and analyze its performance to identify underperforming segments and address any issues in them.

Our data scientists use multiple ML algorithms, like decision trees, linear regression, logistic regression, random forests, support vector machines, and KNN for classification, regression, clustering and dimensionality reduction to build AI models.

Our data scientists select and curate labeled data for training AI models. They choose the appropriate model architecture, define the loss function and optimization algorithm and tune the model’s hyperparameters for optimal performance.

We select a pre-trained model that has been trained for a task similar to the one at hand. Our data scientists design and curate the dataset for fine-tuning the model and tuning the model’s hyperparameters for optimal performance.

Our data scientists utilize multiple NLP toolkits such as NLTK and SpaCy and NLP techniques like tokenization, stemming, and lemmatization to identify the root words in text data and simplify the data by breaking it down into smaller components.

Our developers leverage cutting-edge cognitive technologies to deliver high-quality services and tailored solutions to our clients.

Our team extension model is designed to assist clients seeking to expand their teams with the precise expertise needed for their projects.