Contents:

1. Introduction
2. Concept of Elasticity
3. Measuring Elasticity: Linear Regression
4. Example: Data & Code
5. Dynamic Pricing in Competition: Game Theory
6. Nash Equilibrium

Introduction

One of the biggest challenges in e-commerce is to utilize data mining methods for the improvement of their dynamic pricing policies. Usually these products…

Introduction

We introduced Nash Equilibrium solution concept in the previous blog. In this blog we will start with a continuous action example and we will discuss the applicability of Nash equilibrium in mixed strategies.

Mixed strategies are class of games where player chooses actions stochastically( i.e. …

Introduction

Let’s introduce the idea of solution concept in this section. So far we stressed on representation of payoff for different combinations of unique player’s decisions in the strategic environment. These representations are useless until we apply some model to predict the decision of a given player considering the anticipated decisions…

This is an advanced theoretical blog which focusses on one of the most intriguing and complex aspect of policy gradient algorithms. The reader is assumed to have some basic understanding of policy gradient algorithms: A popular class of reinforcement learning algorithms which estimates the gradient for a function approximation. …

Series

1. NLP Zero to One: Basics (Part 1/30)
2. NLP Zero to One : Sparse Document Representations (Part 2/30)
3. NLP Zero to One: Deep Learning Theory Basics (Part 3/30)
4. NLP Zero to One: Deep Learning Training Procedure (Part 4/30)
5. NLP Zero to One: Dense Representations, Word2Vec (Part 5/30)
6. NLP Zero to One…

Thanks for responding. Its h(planks)/(2*pi). 6.6/(2*3.14) ~ 1.05 ! I will leave a comment in the code.