ORIE 5270

ORIE 5270

Course information provided by the Courses of Study 2018-2019.

This course offers a broad overview of computational techniques and mathematical skills that are useful for data scientists. The course is designed as a "boot camp" to offer students an intensive immersion into the subject over a short period of time. The topics include: unix shell, version control: Git, iPython, creating web APIs, data structures and algorithms, working with databases, exploratory data analysis: using Python and related libraries to explore data sets (pandas, bokeh), Map-Reduce, Spark, Hadoop, overview of some machine learning and optimization algorithms (logit regression, Poisson regression, k-means, neural networks, stochastic gradient descent, gradient descent, lbfgs), Python libraries for data analysis (scikit-learn, pytorch, SciPy, numpy), parallel computing, unit testing, IEEE 754 (Infinity, NaN, rounding error, overflow and underflow).

When Offered Spring.

Permission Note Enrollment limited to: ORIE MEng students.

View Enrollment Information

Syllabi: none
  •   Regular Academic Session. 

  • 2 Credits Graded

  • 18173 ORIE 5270   LEC 001

    • TR Cornell Tech
    • Aug 21 - Aug 22, 2018
    • Toscano Palmerin, S

  • Taught in Cornell Tech in NYC, Enrollment limited to: MEng Financial Engineering students.