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Machine learning basic specification.

Short description

Basic machine learning specification. Includes six course. Contains basic approaches and algorithms for machine learning.

Courses description

  • 1 course - Contains mathematical and programing basis.
  • 2 course - Supervised learning. Includes linear algorithms, regularization, metrics, overfitting and underfitting problems and etc.
  • 3 course - Unsupervised learning. Includes clusterization algorithms, metrics, text processing and thematic modeling.
  • 4 course - Statistics. Includes introduction into statistical approaches.
  • 5 course - Data analysis applications. Business which can be solved by machine learning approach.
  • 6 course - Final projects

Projects description

  • 1 Project - Identification user on the internet. Data - list of user's sessions. Target - User id.

  • 2 Project - Chunk analyze. Data - Dataset of user one company. Target - Users which will stop use the company serves.

  • 3 Project - Time series prediction. Data - Count of rides in New York for 1 year (2016). Target - How many taxi will be needed in each New York district.

  • 4 Project - Text semantic analyze. Data - Users review. Target - Classification on positive and negative.