Machine Learning

Machine Learning vs AI

  • AI aims to help machine carry out task, whereas Machine Learning aims to identify patterns in the data
  • AI are broadly categorized into 2 buckets - generalized and applied.
  • Applied AI is focussed to solve a specific task - for example, wealth management, autonomous car
  • Generalized AI - "one ring that that will rule them all" ... well, we are not there yet!
  • What factors are pushing forward the development in Machine Learning today?
    • Realization that machines can instructed to learn by themselves using data
    • Abundance of available data that can fodder the machines


Neural Network

A computer system designed to work like human brain to classify information. It is used to solve some of these tough

  • Infer the author's sentiment behind piece of text
  • Whether a piece is music is likely to make one happy or sad
  • Infer the meaning of natural language in the form of text or audio


AI And Machine Learning Use Cases

  • Data Security - identify the pattern of data access of malware to detect breaches
  • Personal Security - analyze security security screenings at airports, large gathering to identify threats as much faster rate and higher accuracy than human screeners
  • Financial Trading - find which stocks will rise and which will fall
  • Healthcare - understand the risk factors of diseases in large population, media diagnostics
  • Marketing - personalized ad targeting on web properties
  • Fraud Detection - identity and prevent fraudulent transactions in e-commerce and banking
  • Recommendation - product / service recommendation
  • Search - refine searches based on the context, search history and user profile
  • Natural Language Processing - simplify the essential meaning of a text for fast consumption


Github Repo with code solutions

In the above repositories you can see code examples for the following case studies

  • Estimation for insurance premium based on the customer demographic information
  • House price prediction problems based on Kaggle competition data
  • Power demand forecasting based
  • Stock price forecasting using time series analysis
  • Credit risk assessment
  • Credit card transaction fraud detection
  • Predict customer participation of bank marketing campaign
  • Ad-click prediction using web analytics
  • Customer churn prediction for tele comm customers
  • Segmentation of retail customers
  • OCR - image classification
  • Image classification using cutting edge deep learning for high accuracy
  • Detection of DOS attack using the netflow data
  • Sentiment analysis
  • Movie recommendation