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Machine Learning Use Cases in Real Life

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The power to Think, Decide and Act based on situation, emotion and person is something that makes Human a very unique species in the ecosystem.

Machine Learning is like building the Human type of behavior in a Non-liven Object/Machine/System  based on some highly rich and complex algorithms and  techniques.

Machine Learning helps me what I should take an fits my taste before I myself realize and ask for the same.

Before deep-diving into the details and granularity of the  Machine Learning features. Let’s get a feel and heads up – where in our day-to-day real life Machine Learning is important and makes sense :

  • Banking / Retail / Telecommunication
    • Prospective Customers and Partners
    • Satisfactory index of the Customer (based on relationship, transaction, marketing campaign etc.)
    • Fraud, Waste and Abuse of Claims
    • Forecasted Credit Risk and credibility of the customer
    • Effectiveness of a Marketing Campaign
      • Eg: How many accepted the offer and how many rejected it. Any decisive factors leading to acceptance.
    • Cross Selling and Recommendations
      • Eg: Ecommerce sites : People who purchased this product also purchased this
    • Contact Center (helps the CSR to engage the customer during the call with the relevant data)
      • Eg: We have seen that you have ordered the cheque books to a separate address (different from the registered address) – would you like to change your Address Details
  • Healthcare & Life sciences
    • Scanning & Screening –  Biometrics
    • Drug Discovery based on the component mix
    • Diagnosis and remediation based on the Symptoms, Patient Record and Lab Reports
    • AECP – Adverse Event Case Processing Scenarios based on drug, patient, geo, climatic conditions, past history, food intake etc.
  • General
    • Handwriting to Text or Speech (Identification & Learning Graphology Techniques)
    • Debugging, Troubleshooting and Solution Wizard
    • Email filtering based on Spam
    • Text & Mail categorization/recommendation
    • Support Issues and enriching KeDBs (Knowledge Error Databases)
    • Friends and Colleagues Recommendation – via Facebook, LinkedIn, Twitter etc.
    • Self-Driving Cars – by building artificial intelligence and algorithms
    • Image Processing
  • Security
    • Handwriting / Signature / Fingerprint / Iris / Retina Verification
    • Face Recognition
    • DNA Pattern Matching

(Feel free to suggest and help me enrich this list based your experience and the real time scenarios you have witnessed)

Key Pointers:

  • Building something with a machine/non-living object which is a replica of human brain and that caters to meet the brains of millions and billions of users – is NOT an EASY job.
  • A Rich Volume, Quality Data and Flawless Algorithm is very critical for building/training a Machine Learning Model to think/decide/act like humans do.
  • With millions/billions of non-stop data processing – human mind can get fatigue/tired. At times the Human factor also creates a “Dependency“. This is where Machine Learning Algorithms play a crucial role. Build once and automate it.
  • In simple words : “Big Data + Machine Learning = Deadly Duo

Stay Tuned and Watchout for this space for Detailed Blogs/Notes/Links on Deep Diving Machine Learning. Till then Thanks for Stopping By.

Happy Learning!! 🙂

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