using markov decision process (MDP) to create a policy – hands on – python example
Hello there, i hope you got to read our reinforcement learning (RL) series, some of you have approached us and asked for an example of how you could use the…
using custom transformers in your machine learning pipelines with scikit-learn
Hey there, are you a data scientist or a data analyst? if you are, I bet you’ve heard of the "scikit-learn" library, and probably it is one of your primary…
Social Network Analysis (SNA) In A Connected World
We are all connected, no matter if you want to or not, you probably been interacting with some other individual in the course of your life. In fact, the average…
Reinforcement learning series – getting the basics – part 3
In the previous part we’ve learned about the standard formulation setting of RL (MDP): https://g-stat.com/reinforcement-learning-series-getting-the-basics-part-2. This article would be about a basic method in RL - Monte-Carlo (MC). As stated in…
Not Anything That glitters Is Gold
Let me know if you had this issue before, you a business problem which is data driven, so you think approaching the problem with a data driven solution. You start…
Reinforcement learning series – getting the basics – part 2
Last time we’ve tipped our feet in the water and got some understanding of the basic terminology of the RL world: https://g-stat.com/reinforcement-learning-getting-the-basics-series/. In this article we would learn about Markov Decision…
Customer Segmentation Using Factor Analysis Mixed Data (FAMD) and K-Means
Hey, I bet you wanted to cluster a population sometime, you know, like taking data of a population and to divide it into groups, where in each group the individuals…
Reinforcement learning series – getting the basics
Reinforcement learning (RL) is a rising field in the Machine learning (ML) scene. in this article we will understand what is RL, what problems we can solve with RL and…