Publish to my blog (weekly)

• Use cases of Different Machine Learning Algorithms – Noteworthy - The Journal Blog

  • sales forecasting
  • risk assessment analysis in health insurance companies
  • 1. To Identifying risk factors for diseases and planning preventive measures
  • 2. Classifying words as nouns, pronouns, and verbs
  • 3. Weather forecasting applications for predicting rainfall and weather conditions
  • 4. In voting applications to find out whether voters will vote for a particular candidate or not
  • a user wants to look for similar items in comparison to others.
  • handwriting detection applications
  • image/video recognition tasks.
  • stock analysis
  • image classification
  • comparing the relative performance of stocks over a period of time
  • data exploration
  • option pricing in finances
  • pattern recognition
  • risk trends
  • identifying disease
  • finding out whether a loan applicant is low-risk or high-risk
  • predicting the failure of mechanical parts in automobile engines
  • predicting social media share scores and performance scores
  • automatically classify web pages
  • log snippets
  • forum posts
  • tweets without manually going through them
  • document classification
  • disease prediction
  • sentiment analysis projects
  • spam filters
  • indexing relevancy scores
  • ranking pages
  • classifying data categorically
  • stock market predictions
  • gene expression analysis
  • in pattern classification tasks that ignore class labels
  • detecting different activity types in motion sensors
  • grouping images into different categories
  • for monitoring whether tracked data points changes between different groups over time
  • classifying persons based on different interests
  • segmenting data by purchase history
  • grouping inventories by manufacturing and sales metrics
  • an unsupervised Machine Learning Algorithm
  • K being the number of groups
  • The algorithm filters information and identifies groups with similar tastes to a target user and combines the ratings of that group for making recommendations to that user
  • It makes global product-based associations and gives personalized recommendations based on a user’s own rating.
  • colorization of black and white images
  • handwriting analysis
  • computer vision processes
  • describing or captioning photos based on visual features.
  • feed-forward Neural networks which take in fixed inputs and give fixed outputs
  • image feature classification
  • video processing tasks.
  • they take in arbitrary length sequences and use time-series information for giving outputs
  • text and speech analysis
  • language processing tasks

• Mix Tasks — Phoenix v1.4.5

  • the module name of the schema
  • the module name of the context
  • a list of column_name:type attributes
  • the resource name

Posted from Diigo. The rest of my favorite links are here.