Momentum AI

Momentum AI automates all steps of data preparation, model training, evaluation, deployment and maintenance of AI based application development. This helps save time, reduce errors, and improve the overall productivity of data engineers and scientists.

How Does Momentum AI Work?

Supported Algorithms

Momentum AI supports a wide variety of machine learning algorithms out of the box. It provides pluggable architecture to add new algorithms with just a few simple configurations. Here is a high level list of model that we support:

Classification and Regression

  • Linear and logistic regression
  • Decision tree
  • Random forest
  • Linear support vector (LVM)
  • Deep learning/ Multilayer perceptron/ artificial neural networks
  • Recurrent neural networks/ LSTM
  • Naive Bayes
  • Factorization machines
  • Markov chain

Clustering

  • K-means
  • Latent Dirichlet allocation (LDA)
  • Gaussian Mixture Model (GMM)

Computer Vision

  • Convolutional neural networks
  • Object detection (RCNN, SSD, YOLO)
  • Face recognition
  • LSTM
  • Handwriting recognition (OCR and ICR)

Recommendation Engine

  • Collaborative filtering using alternating least square
  • Explicit feedback
  • Implicit feedback

Classification and Regression

  • Tokenization, segmentation, and sentence classification
  • Parts of speech (POS) tagging
  • Named Entity Recognition (NER)
  • Text Summarization
  • Word2Vec
  • Document Similarity

Feature Engineering

Momentum AI does automatic feature engineering. This helps data scientists to stay focussed on improving the model accuracy. 

You can also perform feature engineering using box plotting, Pearson’s Chi-squared, and correlation coefficients.

If your dataset contains unbalanced classes and downsampling will cause data losses, you could use SMOTE to create synthetic data to balance your classes. Momentum provides a highly scalable SMOTE implementation to work with billions of data rows.

Model Deployment

An efficient versioning, management and deployment of machine learning models are essential for any successful AI implementation. Momentum provides features to easily manage and deploy AI models in production in one of the following deployment use cases: