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Machine learning


Machine Learning

Model Building

Our Data Science team can create aMachine Learning Model based on your business requirement. We can build and train models using supervised, unsupervised and reinforcement learning.

Model Optimization

We optimize the model for maximum accuracy. For optimization, we use hyper-parameter tuning, gradient descent, SGD, ensemble & boosting and many more processes, to derive the best outcomes from the model.

Model Evaluation

To test the performance of Machine Learning Models, we use Cross Validation, RSS, RSME, MSE, Log-loss, F-measure, Precision-Recall etc. to ensure models perform well.

Feature Selection

Our expert team can help you with feature selection using techniques like PCA, LSH, SVD etc., for the best performance from a Machine Learning Model.

Feature Transformation

We are experienced in feature transformation using techniques like PCA, n-gram, Tokenizer, StopWordsRemover, OneHotEncoder, VectorIndexer, Normalizer and much more.

Feature Extraction

Our team has the expertise to deal with raw data using TF-IDF (HashingTF and IDF), Word2Vec, CountVectorizer.