Math for Data Science II

Deal with math at your role as data science dev by intuitive understanding of the concepts

10:00 AM to 5:30 PM, 30 July 2018, Bangalore

Abstract

It is evident that a solid math foundation is indispensible if one has to get into Data science in an honest-to-goodness way. Unfortunately, for many of us math was just a means to get better scores and never really a means to understand the world around us. That systemic failure (education system) causes many of us to feel a “gap” when doing / learning data science. It is high time that we acknowledge that gap and take remedial action.

The purpose of the workshop is to develop an intuitive understanding of the concepts. We let go the fear of rigorous notation and embrace the rationale behind it. The key take away for a participant has to be confidence of being able to deal with any math thrown to them in their role as data science developers.

Pre-requisites

Things to get along: While you won’t need any particular softwares for this workshop, you will need the following:

  • Willingness to think !!
  • A notepad and a pen.
  • Courage to walk up to the board to show your awesome solutions to every one else !
  • A device with a browser and internet .. preferably bigger screens, but mobiles can do as well.

Outline

This workshop is a day-long immersive experience. We will explore following areas:

  1. Indices and Logarithms
  2. Functions as transformations
  3. Complex functions as composition of simpler functions
  4. Polynomials and shapes of polynomial functions
  5. Calculus (with applications to data science problems) The concept of derivatives. Formal definition and the intuitive understanding in n-dimensional space. Techniques for finding derivatives of complex functions. Integration - Formal definition and intuitive understanding. Integral as anti-derivative.
  6. Linear Algebra (with the focus on data science applications) Vectors Matrices as linear transformations of space Concept of span of a vector. Conceptual understanding of Eigen Values and Eigen Vectors

Target Audience

  • Developers who feel rusty with math and want to learn it anew
  • Managers / testers who need to understand what their team members are talking about.
  • Anyone who wishes to get into data science projects but sees math as the obstacle. Participants don’t need to know any math apart from basic +,-, x, / operations.

Instructors


Vishal Gokhale

Software Engineer, AgileFAQs

Tickets

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