Innovating with AI - Onepoint - Do data better | Innovate with AI & more | Solve with design thinking

Innovating with AI

Innovating with AI

Machine learning (ML) algorithms and techniques help in implementing processes that can make intelligent decisions and detect hidden patterns. This provides meaningful insights and logical automation of tasks. 

 

Learning methodologies like supervised or unsupervised learning, neural networks-based deep learning and reinforcement learning can help perform a variety of tasks such as classification, regression, clustering, pattern detection, predictions etc. These methods are geared towards learning models from historical data, which can then be used for various applications on current data.

Applications

  • Image classification, segmentation etc.
  • NLP (Natural Language Processing) based applications
  • Price & sales optimisations
  • Customer services and sentiment analysis
  • Security & threat analysis
  • Smart lead generation
  • Smart data cataloguing
  • ……. many more

Benefits

  • Minimises human intervention
  • Works exceptionally 
  • well on multi-dimensional data
  • Quickly  identifies trends and patterns

Considerations

  • Requires a good amount of quality data for good results
  • Requires tuning and research time to achieve accuracy and precision
  • May need additional compute resources

Our offerings

ML (Machine Learning) use case - Proof of Concept (POC)

  • Analyse ML-based use case requirements 
  • Analyse datasets required to solve the use case
  • Iteratively – select an appropriate algorithm, train model on a dataset, test accuracy of the model, fine-tune the model
  • Evaluate, select and implement the right ML tool which can solve the case

Automated data management

  • ML can be used on data management processes like MDM, cataloging etc to gain intelligent and automated insights
  • Gauge the benefits of such processes through PoCs

Technologies

Python - Most popular language for ML/AI with extensive libraries and tools like Jupyter notebooks

Open source library for Deep Learning

A research institute dedicated towards Deep Learning

Deep Learning Library on Python

Open source ML library

Distributed engine also popular for ML

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