Les 10 concurrents ariseanalytics.com les plus visités

jitsu.com

How modern data warehouses are used to build a single source of truth

g-stat.com

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 power of RL to real life. for that reason we decided to create a small example using python which you could copy-paste and implement to your business cases. for us to move forward you have to make sure you know all the prerequisite needed to start using RL methodology, so for a quick recap go through this blog post we wrote a couple of months ago: https://g-stat.com/reinforcement-learning-getting-the-basics-series/. Just a quick reminder, MDP, which we will implement, is a discrete time stochastic control process. It provides a mathematical framework for modeling decision making in situations where outcomes are partly random and partly under the control of a decision maker. Markov Decision Processes are a tool for modeling sequential decision-making problems where a decision maker interacts with the environment in a sequential fashion. So, the problem we have in front of us goes like this, we have a world of 12 states, 1 obstacle initial state (state 5) and an 2 end states (states 10, 11). for each state we have a reward, we want to find the policy to implement for best reward accumulation. for each state the reward -0.04 (r=-0.4). and for the state 10 it's +1 and for end state 11 the reward is -1. For each state we are in, we want to find the best action, should we go North (N), South (S), East (E) or West(W). basically we want to get to state 10 and in the shortest way possible. first of all let's create a World class, which will be used our world for the problem, the world class is written in here: https://github.com/houhashv/MDP/blob/yossi/World.py. this object could help us declare the world, plot it and to plot the policy we found to move side the world. the method plot_world plots the image we saw above. By the way we are about to solve this problem is by using value iteration as compared to policy itera

brainforge.ai

Learn how to set up Amplitude tracking the right way. Avoid data mess with our step-by-step guide to event tracking and user behavior analytics.

analytics-debugger.com

Debug 20+ analytics vendors in real-time with our free Chrome extension.

grapheverywhere.com

Participa en el webinar "Optimizando las Operaciones IT con grafos: Caso de uso BBVA – Smart Deploy Applications"

datamesh-architecture.com

Is data mesh something for your company right now? Find out in our fitness test

jamesserra.com

The top questions I am seeing from customers looking to build a modern data warehouse in the cloud, and the blogs that I have wrote that try to answer the question.

inspari.dk

Formålet er at give en dybdegående indsigt i de mange muligheder, som Power BI giver inden for business intelligence. Tilmeld dig kursus i Power BI.