Camilo Rocha @HQuilo

15. Lugares donde la ciudadanía por derecho de nacimiento se basa en la tierra y lugares donde se basa en la sangre

𝐂𝐎𝐍𝐎𝐂𝐄 𝐀 𝐃𝐀𝐕𝐈𝐃 𝐆𝐎𝐍𝐙𝐀́𝐋𝐄𝐙 📖🔎 Hablaremos sobre su: • Formación. • Trayectoria. • Sistemas tácticos. • Estilos de juego. • Virtudes y desventajas. Abro🧵 likes y rt’s se reciben.

Hoy la @javerianacali se renueva con la llegada de los Neojaverianos/as que se preparan para ser los mejores profesionales para el mundo. Que su experiencia universitaria sea un camino transformador que les impulse a la construcción de una sociedad justa, sostenible e incluyente.

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Today we were awarded the Andesco Sustainability Award in the environmental category. This recognition reflects the importance of our work in contributing to a better 🌎.

Javeriana Cali @javerianacali

2 years ago

#OrgulloJaveriano 💙 | Nuestro Instituto de Investigación en Ciencias @Omicas_, ha sido galardonado con el Premio Andesco a la Sostenibilidad ♻️. Este reconocimiento destaca nuestra labor en mejorar la seguridad alimentaria y la sostenibilidad del agro👏🏼 bit.ly/3VZHDyu

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El desarrollo de la @javerianacali se da al poner el conocimiento al servicio de la sociedad a través de profesionales íntegros. Hoy reconocemos a los profesores javerianos, quienes desde la integración del servicio, la docencia y la investigación forman los mejores para el mundo

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This study employs an improved version of the CSI-OC methodology, which with diverse data types and uses a Lasso-based network to identify stress-responsive genes. The objective is to identify drought stress-relevant genes in Colombian sugarcane cultivars. sciencedirect.com/science/articl…

🍺 American’s favorite beers by generation: MILLENNIALS 1. Heineken 2. Modelo 3. Corona 4. Corona Extra 5. Corona Light 6. White Claw 7. Guinness 8. Stella Artois 9. Budweiser 10. Miller GEN X 1. Guinness 2. Heineken 3. Corona 4. Modelo 5. Samuel Adams 6. Stella Artois 7. Corona Extra 8. Corona Light 9. Blue Moon 10. Miller BOOMER 1. Guinness 2. Heineken 3. Corona 4. Samuel Adams 5. Coors 6. Miller 7. Michelob Light 8. Miller Lite 9. Dos Equis 10. Stella Artois According to YouGov

Así vivimos la carrera @coBERCHMANScali, celebrando sus 90 años 🎉 junto a toda la comunidad javeriana y caleña 🤩 Un recorrido por nuestro campus donde se desafiaron a correr 🏃‍♀️2k, 5k y 10k 🙌🏼 Apoyamos la vida, la salud y bienestar 🍃😌✨

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Number of Super Bowl wins, by country: 🇺🇸 USA: 58 🇨🇦 Canada: 0 🇦🇺 Australia: 0 🇨🇳 China: 0 🇮🇳 India: 0 🇯🇵 Japan: 0 🇬🇧 UK: 0 🇷🇺 Russia: 0 🇩🇪 Germany: 0 🇪🇸 Spain: 0 🇮🇹 Italy: 0

Te presentamos los elementos de la tabla periódica ilustrada con sus principales aplicaciones en la vida real. Los que desean tener en alta resolución pueden descargarlo en el primer comentario gratis.

Con dolor registramos hoy el fallecimiento por múltiples quemaduras y absorción de gases tóxicos provenientes de un incendio fuera de control del carismático frailejón Ernesto Pérez Buitrago a sus 31 años de edad. Homenaje en este 🧵

Most Corrupt Countries in the World ( Lower scores denote higher corruption ): 🇸🇴 Somalia: 12 🇸🇾 Syria: 13 🇸🇸 South Sudan: 13 🇻🇪 Venezuela: 14 🇾🇪 Yemen: 16 🇰🇵 North Korea: 17 🇧🇮 Burundi: 17 🇭🇹 Haiti: 17 🇱🇾 Libya: 17 🇬🇶 Equatorial Guinea: 17 🇹🇩 Chad: 19 🇹🇲 Turkmenistan: 19 🇰🇲 Comoros: 19 🇬🇼 Guinea Bissau: 21 🇸🇩 Sudan: 22 🇪🇷 Eritrea: 22 🇲🇲 Myanmar: 23 🇮🇶 Iraq: 23 🇿🇼 Zimbabwe: 23 🇭🇳 Honduras: 23 🇦🇿 Azerbaijan: 23 🇳🇬 Nigeria: 24 🇦🇫 Afghanistan: 24 🇬🇹 Guatemala: 24 🇰🇭 Cambodia: 24 🇹🇯 Tajikistan: 24 🇨🇫 Central African Republic: 24 🇱🇧 Lebanon: 24 🇧🇩 Bangladesh: 25 🇮🇷 Iran: 25 🇬🇳 Guinea: 25 🇺🇬 Uganda: 26 🇲🇿 Mozambique: 26 🇲🇬 Madagascar: 26 🇨🇲 Cameroon: 26 🇱🇷 Liberia: 26 🇵🇰 Pakistan: 27 🇷🇺 Russia: 28 🇲🇱 Mali: 28 🇵🇾 Paraguay: 28 🇬🇦 Gabon: 29 🇪🇬 Egypt: 30 🇵🇬 Papua New Guinea: 30 🇹🇬 Togo: 30 🇲🇷 Mauritania: 30 🇸🇿 Eswatini: 30 🇲🇽 Mexico: 31 🇺🇿 Uzbekistan: 31 🇧🇴 Bolivia: 31 🇱🇦 Laos: 31 🇰🇪 Kenya: 32 🇳🇪 Niger: 32 🇩🇴 Dominican Republic: 32 🇵🇭 Philippines: 33 🇩🇿 Algeria: 33 🇺🇦 Ukraine: 33 🇦🇴 Angola: 33 🇿🇲 Zambia: 33 🇸🇻 El Salvador: 33 🇲🇳 Mongolia: 33 🇮🇩 Indonesia: 34 🇳🇵 Nepal: 34 🇲🇼 Malawi: 34 🇸🇱 Sierra Leone: 34 🇧🇦 Bosnia And Herzegovina: 34 🇬🇲 Gambia: 34 🇹🇷 Turkey: 36 🇹🇭 Thailand: 36 🇵🇪 Peru: 36 🇱🇰 Sri Lanka: 36 🇰🇿 Kazakhstan: 36 🇪🇨 Ecuador: 36 🇷🇸 Serbia: 36 🇵🇦 Panama: 36 🇦🇱 Albania: 36 🇨🇮 Ivory Coast: 37 🇱🇸 Lesotho: 37 🇧🇷 Brazil: 38 🇪🇹 Ethiopia: 38 🇹🇿 Tanzania: 38 🇦🇷 Argentina: 38 🇲🇦 Morocco: 38 🇨🇴 Colombia: 39 🇧🇾 Belarus: 39 🇲🇩 Moldova: 39 🇮🇳 India: 40 🇹🇳 Tunisia: 40 🇲🇰 North Macedonia: 40 🇬🇾 Guyana: 40 🇸🇷 Suriname: 40 🇲🇻 Maldives: 40 🇻🇳 Vietnam: 42 🇧🇫 Burkina Faso: 42 🇭🇺 Hungary: 42 🇰🇼 Kuwait: 42 🇹🇹 Trinidad And Tobago: 42 🇹🇱 Timor Leste: 42 🇸🇧 Solomon Islands: 42 🇿🇦 South Africa: 43 🇬🇭 Ghana: 43 🇸🇳 Senegal: 43 🇧🇯 Benin: 43 🇧🇬 Bulgaria: 43 🇴🇲 Oman: 44 🇯🇲 Jamaica: 44 🇧🇭 Bahrain: 44 🇨🇳 China: 45 🇨🇺 Cuba: 45 🇲🇪 Montenegro: 45 🇸🇹 Sao Tome And Principe: 45 🇷🇴 Romania: 46 🇦🇲 Armenia: 46 🇲🇾 Malaysia: 47 🇯🇴 Jordan: 47 🇻🇺 Vanuatu: 48 🇳🇦 Namibia: 49 🇭🇷 Croatia: 50 🇲🇺 Mauritius: 50 🇸🇦 Saudi Arabia: 51 🇷🇼 Rwanda: 51 🇲🇹 Malta: 51 🇬🇷 Greece: 52 🇨🇾 Cyprus: 52 🇬🇩 Grenada: 52 🇸🇰 Slovakia: 53 🇫🇯 Fiji: 53 🇨🇷 Costa Rica: 54 🇵🇱 Poland: 55 🇱🇨 Saint Lucia: 55 🇩🇲 Dominica: 55 🇮🇹 Italy: 56 🇬🇪 Georgia: 56 🇸🇮 Slovenia: 56 🇶🇦 Qatar: 58 🇱🇻 Latvia: 59 🇪🇸 Spain: 60 🇧🇼 Botswana: 60 🇻🇨 Saint Vince 🇵🇹 Portugal: 62 🇱🇹 Lithuania: 62 🇰🇷 South Korea: 63 🇮🇱 Israel: 63 🇧🇸 Bahamas: 64 🇧🇧 Barbados: 65 🇨🇱 Chile: 67 🇦🇪 United Arab Emirates: 67 🇹🇼 Taiwan: 68 🇧🇹 Bhutan: 68 🇺🇸 United States: 69 🇸🇨 Seychelles: 70 🇦🇹 Austria: 71 🇫🇷 France: 72 🇯🇵 Japan: 73 🇬🇧 United Kingdom: 73 🇧🇪 Belgium: 73 🇨🇦 Canada: 74 🇺🇾 Uruguay: 74 🇪🇪 Estonia: 74 🇮🇸 Iceland: 74 🇦🇺 Australia: 75 🇭🇰 Hong Kong: 76 🇮🇪 Ireland: 77 🇩🇪 Germany: 79 🇳🇱 Netherlands: 80 🇨🇭 Switzerland: 82 🇸🇪 Sweden: 83 🇸🇬 Singapore: 83 🇳🇴 Norway: 84 🇫🇮 Finland: 87 🇳🇿 New Zealand: 87 🇩🇰 Denmark: 90 Source: World population review

Annual inflation rate. 🇻🇪 Venezuela: 283% 🇱🇧 Lebanon: 212% 🇦🇷 Argentina: 161% 🇹🇷 Turkey: 61.9% 🇮🇷 Iran: 39.2% 🇪🇬 Egypt: 34.6% 🇵🇰 Pakistan: 29.7% 🇳🇬 Nigeria: 28.2% 🇰🇿 Kazakhstan: 10.3% 🇨🇴 Colombia: 10.1% 🇩🇿 Algeria: 8.2% 🇭🇺 Hungary: 7.9% 🇷🇺 Russia: 7.5% 🇵🇱 Poland: 6.6% 🇸🇪 Sweden: 5.8% 🇮🇳 India: 5.55% 🇿🇦 South Africa: 5.5% 🇦🇺 Australia: 5.4% 🇦🇹 Austria: 5.3% 🇺🇦 Ukraine: 5.1% 🇳🇴 Norway: 4.8% 🇧🇷 Brazil: 4.68% 🇲🇽 Mexico: 4.32% 🇦🇪 UAE: 4.27% 🇵🇭 Philippines: 4.1% 🇮🇪 Ireland: 3.9% 🇬🇧 UK: 3.9% 🇸🇬 Singapore: 3.6% 🇫🇷 France: 3.5% 🇫🇮 Finland: 3.3% 🇮🇱 Israel: 3.3% 🇰🇷 South Korea: 3.2% 🇩🇪 Germany: 3.2% 🇪🇸 Spain: 3.2% 🇺🇸 US: 3.1% 🇨🇦 Canada: 3.1% 🇯🇵 Japan: 2.8% 🇮🇩 Indonesia: 2.61% 🇸🇦 Saudi Arabia: 1.7% 🇳🇱 Netherlands: 1.6% 🇲🇾 Malaysia: 1.5% 🇨🇭 Switzerland: 1.4% 🇮🇹 Italy: 0.67% 🇩🇰 Denmark: 0.6% 🇹🇭 Thailand: -0.4% 🇨🇳 China: -0.5%

Felicitaciones a la Dra. Ivonne Leadith Díaz Pérez, quien hoy se posesionó como nueva Decana de la Facultad de Humanidades y Ciencias Sociales, un reconocimiento a su formación, su aprecio y asimilación del proyecto educativo de la @javerianacali

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#NoticiaJaveriana 🗞 | Ivonne Leadith Díaz 👩🏼‍🦱 , es la nueva decana de la Facultad de Humanidades y Ciencias Sociales 🙌🏼 Felicitamos a la decana por esta nueva etapa en su vida académica y profesional y auguramos una gestión muy exitosa 👏🏼. javerianacali.edu.co/noticias/ivonn…

9302023 is a prime number it also happens to be today's data in mm/dd/yyyy format

Every Data Scientist needs to know these ideas. They will blow your mind. 1. Correlation vs Causation P(A | B) is the probability of A given B. It is the probability that we will observe A given that we have already observed B. P(A | do(B)) is the probability of A given do(B). It is the probability that we will observe A given that we have intervened to cause B to happen. In this context, an intervention simply means to take an action of some kind. Therefore do(B) means to take an action which causes B to happen. The expressions P(A | B) and P(A | do(B)) might seem very similar but they represent very different situations. 2. We can only learn P(A|B) from the data alone. Bob has an extremely accurate weather app and is always very good about bringing his umbrella when it rains. We observe Bob over several years and we find that whenever it rains, Bob always has his umbrella and he never brings his umbrellas on days when it doesn't rain. In the language of probability, we say P(Umbrella | Rain) = 1 and P(Rain | Umbrella) = 1 as well. What we can learn from this data alone is how to predict whether it rains with a 100% accuracy by checking whether Bob has an umbrella. We can also learn to predict with 100% accuracy whether Bob has an umbrella by checking if it's going to rain. What we cannot learn is what will happen if we give Bob an umbrella on a random day of our choosing. The answer to this question is P(Rain | do(Umbrella) ) and it's unknowable from the data alone. We need prior knowledge about how the world works to properly interpret the data we collected. We need to know that rain has an effect on Bob's behavior, but Bob's behavior has no effect on the rain. Information about the effects of interventions are simply not available in raw data unless it is collected by controlled experimental manipulation. 3. Scientific Experiments work because they produce a very special kind of data. You may have heard of what many people call a scientific experiment. Take a collection of objects, animals or people. Randomly split that collection into a control group and a treatment group. Apply your intervention to the treatment group while leaving the control group alone. If you observe any differences between the treatment group and the control group, it is logical to attribute these differences to the treatment. You can therefore say the differences were caused by the treatment. In statistics, the procedure I just described is called a Randomized Controlled Trial. It is a procedure for generating a specific kind of data where: P(Difference | Treatment) = P(Difference | do(Treatment) ) This is why traditional science experiments work. They are designed to capture causal information. This is not the case for vast majority of data that we collect in society. Without human guidance or access to real world knowledge, statistical algorithms and artificial intelligences can only learn P(A | B) from the raw data. This is a fundamental mathematical limitation on the use of data alone. That's it for now. This post is part of a series of posts about the concept of causal inference. They are based on the content of the Book of Why by Judea Pearl with lots of commentary from me. Follow me (@kareem_carr) so you don't miss out on the next post. Please show support by liking and retweeting the thread.

theLinuxRevoultionHasAlreadyBegun reddit.com/r/programmerhu…

@javerianacali galardonada con el Premio Bienal de Investigación en el área de ciencias naturales, medio ambiente e ingeniería. javerianacali.edu.co/noticias/profe…. @vicdurcas @IngridSchuler

Housing Overcrowding (%) Colombia🇨🇴: 34.6 Latvia🇱🇻: 34 Mexico🇲🇽: 31 Poland🇵🇱: 28.4 Türkiye🇹🇷: 23.8 Italy🇮🇹: 19.4 Greece🇬🇷: 18.2 Sweden🇸🇪: 14.4 Finland🇫🇮: 9.3 Estonia🇪🇪: 8.9 France🇫🇷: 7.6 Korea🇰🇷: 4.7 USA🇺🇸: 4.2 Spain🇪🇸: 3.7 Ireland🇮🇪: 3.4 Japan🇯🇵: 1.6 UK🇬🇧: 0.8 NZ🇳🇿: 0.7 @OECD