Identifying the principal features
Identification of features that matter is one of the most important steps in getting a model that can solve real problems. Using your data, our team does an end to end analysis, checking hundreds of data points that could be relevant.
Understand and clean your data
In this exercise, each data point or feature is cleaned up, normalized and fine tuned for usage in training the models. We have worked with Text, Numeric, Images as well as signals from devices and used them in training highly successful models.
Identify linear / non - linear models
We have developed an algorithm than can identify the perfect model to solve your problem. We can advise you on whether you should use a Neural Network or a Support Vector machine to solve your problem.
Train, Cross-validate and Test
We can train and retrain your models improving with every batch. With access to on demand machine learning on the cloud and our holistic learning approach, we can get you 80%-90% prediction accuracy in a very short amount of time.
Most often the biggest dilemma that happens during model training is what hyper parameter set to use. How do you know what is best and how to validate if this is the best setting. With our expertise we can advise you on things like appropriate loss functions, gradients, iterations, regularization values, no of layers etc.
We have worked with customers and helped achieve awesome learning rates for different kinds of models. Algorithms that we support are :
Deep Neural Networks
For non linear problems like image recognition, we can help train a deep neural network for you.
Support Vector Machines
SVM’s achieve high degree of accuracies very soon and can be used for linear classification as well as multiclass problems.
K Means Clustering
For simple clustering problems we can help you train a K Means Clustering model.
Apart from training Java based models from scratch, Constellation works with the following technologies as well :