Study

I am taking classes in our group meeting, online courses websites, etc. This is very helpful on my research, especially when transferring from EE to CS and from networking to machine learning. I would like to share my experiences and notes of these courses.

More materials will come ...

Machine Learning

Machine Learning

  • Linear Regression

  • Classification

    • Naive Bayes Classifier

    • Logistic Regression

    • Support Vector Machine

  • Decision Tree and Random Forest

  • Neural Network

    • Deep Learning

  • Regularizatino and Model Selection

    • Regularization

  • Unsupervised Learning

    • Clustering

    • Expectation-Maximization

    • Associative

Mining of Massive Data Set

Data Structure and Algorithms

Data Structures

  • Arrays

  • Linked Lists

  • Trees

  • Stacks

  • Queues

  • Heap

  • HashMaps

  • Graphs

Algorithms

  • String

  • Sorting

  • Search

  • Greedy

  • Dynamic Programming

Typical Questions

  • Meeting Rooms II (multiple solutions; data structures: ArrayList, MinHeap, TreeMap)