Pablo Gutierrez has not received any gifts yet

Pablo Gutierrez liked Bill Schmarzo's blog post Using Confusion Matrices to Quantify the Cost of Being Wrong

Sep 8, 2020

Pablo Gutierrez's blog post was featured### Entropy of rolling dices

The Entropy is one of the most important concepts in many fields like physics, mathematics, information theory, etc.Entropy is related to the number of states that one stochastic system can take and how this system will evolve with time, in such a way that the uncertainty will be maximized.This will happened y two ways, first, every system will choose the configuration with a higher degree of entropy among all that are available and second, if we let the system evolve, after some time it will…See More

May 21, 2020

Pablo Gutierrez commented on Andrea Manero-Bastin's blog post The 17 equations that changed the course of history

"Very nice post!
I belive that the Shanon equation for information theory is related to the definition of Entropy and its nature, so equations 6 and 9 would be connected."

Apr 16, 2020

Rudy Martin liked Pablo Gutierrez's blog post Nonlinear regression of COVID19 infected cases.

Apr 16, 2020

Pablo Gutierrez commented on Pablo Gutierrez's blog post Nonlinear regression of COVID19 infected cases.

"Hi Jason.
The data is for cumulative cases. Of course most of these people will recover after a while, but the analysis is focused on the infection process.
Regards"

Apr 16, 2020

Roan A Garcia-Quintana liked Pablo Gutierrez's blog post Nonlinear regression of COVID19 infected cases.

Apr 15, 2020

Jason Chia Kim Leng commented on Pablo Gutierrez's blog post Nonlinear regression of COVID19 infected cases.

"This seems to model a scenario where the number of infected COVID-19 cases will plateau eventually instead of decline back down to zero-which suggests that life will never return back to normal...unless the graphical plot’s y axis represents…"

Apr 15, 2020

Pablo Gutierrez commented on Pablo Gutierrez's blog post Nonlinear regression of COVID19 infected cases.

"Thanks Peter. I will check it out. Regards"

Apr 13, 2020

Peter Cotton commented on Pablo Gutierrez's blog post Nonlinear regression of COVID19 infected cases.

"Nice exposition. Thanks. Of course there are some issues with assuming a representative agent. See this post for some discussion of population density etc and simulations using pandemic on PyPI. I'll follow up with a blog…"

Apr 13, 2020

Pablo Gutierrez liked Bohdan Pavlyshenko's blog post Bayesian Model for COVID-19 Spread Prediction

Apr 13, 2020

Habib commented on Pablo Gutierrez's blog post Nonlinear regression of COVID19 infected cases.

"Could you please share the R codes and the data files in English to replicate the results at:
[email protected]"

Apr 12, 2020

Pablo Gutierrez's blog post was featured### Nonlinear regression of COVID19 infected cases.

In 1927, W. O. Kermack y A. G. McKendrick described the first mathematical model for infectious diseases using a set of differential equations. This model is called SIR because of the three states one individual can have. These states are:Susceptible: The individuals that can be infected by the diseaseInfected: The individuals that have been infected and suffer the disease.Recovered: The individuals that recovered from the disease and have become immune.The equations that represent these states…See More

Apr 12, 2020

Pablo Gutierrez's blog post was featured### An easy way to evaluate the probability of winning a commercial opportunity

When ever we visit a client and present our proposal, we start wondering if it will be accepted or rejected by the customer. Usually, our customer will analyze our proposal, compare it with other competitors’ and make a decision.In order to build our commercial forecast system, we need to assign a probability to every proposal we have presented and assign a numerical value to every one of them. One way of doing this is multiplying the value of the proposal by the probability of wining…See More

Nov 29, 2019

- Company:
- Telefonica

- Job Title:
- Analyst

- Seniority:
- Technical

- Job Function:
- Data Science, Machine Learning, Business Analytics, BI

- Industry:
- Telco

- LinkedIn Profile:
- http://https://www.linkedin.com/in/pablogutierrezastilleros/

- Interests:
- Contributing, Networking

Posted on May 21, 2020 at 6:53am 0 Comments 2 Likes

The Entropy is one of the most important concepts in many fields like physics, mathematics, information theory, etc.

Entropy is related to the number of states that one stochastic system can take and how this system will evolve with time, in such a way that the uncertainty will be maximized.

This will happened y two ways, first, every system will choose the configuration with a higher degree of entropy among all that are available and second, if we let the system evolve, after…

ContinuePosted on April 12, 2020 at 11:23am 5 Comments 2 Likes

In 1927, W. O. Kermack y A. G. McKendrick described the first mathematical model for infectious diseases using a set of differential equations. This model is called SIR because of the three states one individual can have.

These states are:

- Susceptible: The individuals that can be infected by the disease
- Infected: The individuals that have been infected and suffer the disease.
- Recovered: The individuals that recovered from the disease and have become…

Posted on November 26, 2019 at 3:05am 0 Comments 0 Likes

When ever we visit a client and present our proposal, we start wondering if it will be accepted or rejected by the customer. Usually, our customer will analyze our proposal, compare it with other competitors’ and make a decision.

In order to build our commercial forecast system, we need to assign a probability to every proposal we have presented and assign a numerical value to every one of them.

One way of doing this is multiplying the value of the proposal by the probability of…

- No comments yet!

© 2021 TechTarget, Inc. Powered by

Badges | Report an Issue | Privacy Policy | Terms of Service

**Most Popular Content on DSC**

To not miss this type of content in the future, subscribe to our newsletter.

- Book: Applied Stochastic Processes
- Long-range Correlations in Time Series: Modeling, Testing, Case Study
- How to Automatically Determine the Number of Clusters in your Data
- New Machine Learning Cheat Sheet | Old one
- Confidence Intervals Without Pain - With Resampling
- Advanced Machine Learning with Basic Excel
- New Perspectives on Statistical Distributions and Deep Learning
- Fascinating New Results in the Theory of Randomness
- Fast Combinatorial Feature Selection

**Other popular resources**

- Comprehensive Repository of Data Science and ML Resources
- Statistical Concepts Explained in Simple English
- Machine Learning Concepts Explained in One Picture
- 100 Data Science Interview Questions and Answers
- Cheat Sheets | Curated Articles | Search | Jobs | Courses
- Post a Blog | Forum Questions | Books | Salaries | News

**Archives:** 2008-2014 |
2015-2016 |
2017-2019 |
Book 1 |
Book 2 |
More

**Most popular articles**

- Free Book and Resources for DSC Members
- New Perspectives on Statistical Distributions and Deep Learning
- Time series, Growth Modeling and Data Science Wizardy
- Statistical Concepts Explained in Simple English
- Machine Learning Concepts Explained in One Picture
- Comprehensive Repository of Data Science and ML Resources
- Advanced Machine Learning with Basic Excel
- Difference between ML, Data Science, AI, Deep Learning, and Statistics
- Selected Business Analytics, Data Science and ML articles
- How to Automatically Determine the Number of Clusters in your Data
- Fascinating New Results in the Theory of Randomness
- Hire a Data Scientist | Search DSC | Find a Job
- Post a Blog | Forum Questions