Giannis Tolios’ Post

𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗦𝗶𝗺𝗽𝘀𝗼𝗻'𝘀 𝗣𝗮𝗿𝗮𝗱𝗼𝘅 🖥️📊 Simpson’s paradox is a statistical phenomenon where the relationship between two variables changes, if the population is divided into subcategories. In the following animation, we can see how the linear relationship between two variables is inversed, when we take into account a third categorical variable. Simpson's paradox highlights the fact that analysts should always be diligent to avoid mistakes. Check the links below for more information, and make sure to follow me for regular data science content! 𝗦𝗶𝗺𝗽𝘀𝗼𝗻'𝘀 𝗣𝗮𝗿𝗮𝗱𝗼𝘅 - 𝗪𝗶𝗸𝗶𝗽𝗲𝗱𝗶𝗮: https://lnkd.in/dUriE_aX 𝗟𝗲𝗮𝗿𝗻 𝗠𝗟 𝗮𝗻𝗱 𝗧𝗦 𝗙𝗼𝗿𝗲𝗰𝗮𝘀𝘁𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗣𝘆𝗖𝗮𝗿𝗲𝘁📚: https://lnkd.in/dyByK4F #datascience #python #statistics #machinelearning #linkedin

𝗖𝗿𝗲𝗮𝘁𝗲 𝗔𝘄𝗲𝘀𝗼𝗺𝗲 𝗣𝗹𝗼𝘁𝘀 𝘄𝗶𝘁𝗵 𝗣𝘆𝘁𝗵𝗼𝗻! 🖥️📊 Have you ever wanted to create amazing visualizations with Python code? The Python Graph Gallery is a website helping you accomplish that, by offering tutorials for various plot types! Furthermore, clicking on each plot provides a brief description, as well as code examples in Matplotlib, Seaborn, Plotly and other visualization libraries. This website is a valuable guide for beginners, as well as experts creating advanced visualizations with Python. Check the links for more information, and make sure to follow me for regular data science content! 𝗣𝘆𝘁𝗵𝗼𝗻 𝗚𝗿𝗮𝗽𝗵 𝗚𝗮𝗹𝗹𝗲𝗿𝘆 𝘄𝗲𝗯𝘀𝗶𝘁𝗲: https://lnkd.in/dxnGBNa9 𝗟𝗲𝗮𝗿𝗻 𝗠𝗟 𝗮𝗻𝗱 𝗧𝗦 𝗙𝗼𝗿𝗲𝗰𝗮𝘀𝘁𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗣𝘆𝗖𝗮𝗿𝗲𝘁📚: https://lnkd.in/dyByK4F #datascience #python #machinelearning #deeplearning #linkedin

𝗧𝗵𝗲 𝗙𝗮𝘀𝗰𝗶𝗻𝗮𝘁𝗶𝗻𝗴 𝗣𝗵𝗲𝗻𝗼𝗺𝗲𝗻𝗼𝗻 𝗼𝗳 𝗘𝗺𝗲𝗿𝗴𝗲𝗻𝗰𝗲! 💡 "The whole is greater than the sum of its parts." This timeless quote by Aristotle, encapsulates the essence of a fascinating phenomenon, that is known as emergence in Systems Science. Emergence is defined as follows: the interactions between a system's parts may result to unpredictable new behavior, that can't be observed on individual entities. In the video below, we can see the movement of a flock of birds (murmuration), commonly used as an example of emergence. Notably, swarm behavior has been modeled mathematically, having many practical applications. There are countless emergent phenomena, from Biology and Physics, to Economics and human societies, making complex systems an important research area. The cause of emergence remains unexplained, but it appears to be a fundamental property of our universe! #science #emergence #datascience #linkedin

I am excited to say that Moez Ali has endorsed my book, Simplifying Machine Learning with PyCaret! Moez is the creator of PyCaret, while also having an impressive background as a developer, educator and content creator in data science. Moez has been extremely helpful and always provided valuable feedback, so I would like to thank him for the support! You can check the link below for more information, and make sure to follow me for regular data science content. 𝗦𝗶𝗺𝗽𝗹𝗶𝗳𝘆𝗶𝗻𝗴 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗣𝘆𝗖𝗮𝗿𝗲𝘁: https://lnkd.in/dyByK4F #python #datascience #machinelearning #deeplearning #linkedin

𝗛𝗼𝘄 𝗘𝗰𝗹𝗶𝗽𝘀𝗲𝘀 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗦𝗰𝗶𝗲𝗻𝗰𝗲! ☀️ Today around 19:00 UTC, a total solar eclipse will take place, being visible in the USA, Canada and Mexico. Apart from the impressive spectacle, solar eclipses have provided valuable insights to scientific research. A century ago, the british astronomer Arthur Eddington was able to gather empirical evidence for the General Theory of Relativity, which had been introduced a few years earlier by Albert Einstein. Eddington took advantage of the total solar eclipse occurring during that time, to verify whether General Relativity predictions were accurate. According to Eddington's observations, light coming from distant stars deviated from its course, due to the spacetime curvature caused by the Sun. This was a triumph for Einstein, who became an iconic figure of the 20th century, leaving his timeless mark on Physics. Furthermore, this event was monumental for scientific progress, as the limits of classical mechanics established by Newton several centuries before, were surpassed. The combination of scientific theory and experimental validation, fundamentally changed our perception about the universe! #science #physics #eclipse #linkedin

𝗘𝘅𝗽𝗹𝗼𝗿𝗶𝗻𝗴 𝘁𝗵𝗲 𝗟𝗶𝗺𝗶𝘁𝘀 𝗼𝗳 𝗛𝘂𝗺𝗮𝗻 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲! 💡 Kurt Gödel was a logician and philosopher, widely recognized for his important contributions to mathematical logic and the foundations of mathematics, during the 20th century. Gödel's most significant achievements include his incompleteness theorems, which demonstrated the inherent limitations of formal systems capable of basic arithmetic. In addition, Gödel's contributions extended beyond those theorems, impacting various areas of logic and mathematics, hence establishing him as one of the most significant logicians in history. Furthermore, Gödel was a scholar at the Institute for Advanced Study of Princeton, alongside prominent scientists, including Albert Einstein, Robert Oppenheimer and John von Neumann. Formal systems are mathematical frameworks that can be used to infere theorems, based on a set of axiomatic truths. Gödel's incompleteness theorems revealed inherent limitations within such systems, indicating that any formal system capable of arithmetic, contains true statements that are impossible to prove. Specifically, the first incompleteness theorem states that in a formal system, there exist true propositions that can't be proven based on the axioms of this system. His second theorem expanded this idea, by indicating that such systems cannot demonstrate their own consistency. Those discoveries had radical implications, as they affected not only mathematics but also computer science and other scientific disciplines. Furthermore, Gödel's work had another profound effect, practically establishing an insurmountable limit to human knowledge! 𝗛𝗼𝘄 𝗚ö𝗱𝗲𝗹’𝘀 𝗣𝗿𝗼𝗼𝗳 𝗪𝗼𝗿𝗸𝘀: https://lnkd.in/ducGhpmB #science #mathematics #philosophy #linkedin

𝗚𝗲𝘁 𝗮 𝗙𝗥𝗘𝗘 𝗣𝘆𝘁𝗵𝗼𝗻 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗕𝗼𝗼𝗸! 🖥️💡 An Introduction to Statistical Learning is one of the most popular machine learning books, being studied by millions of people across the world. This book introduces all theoretical concepts, including regression, classification, decision trees, clustering, deep learning and more. The book has been updated to include Python code examples, but you can also get the R version if preferable. Furthermore, both books are freely available to download in PDF format! Check the links for more information, and make sure to follow me for data science content. 𝗔𝗻 𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝘁𝗼 𝗦𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝗮𝗹 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴: https://lnkd.in/eEdx_Q2a 𝗟𝗲𝗮𝗿𝗻 𝗠𝗟 𝗮𝗻𝗱 𝗧𝗦 𝗙𝗼𝗿𝗲𝗰𝗮𝘀𝘁𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗣𝘆𝗖𝗮𝗿𝗲𝘁📚: https://lnkd.in/dyByK4F #datascience #python #machinelearning #deeplearning #linkedin 

𝗖𝗿𝗲𝗮𝘁𝗲 𝗘𝘅𝗽𝗹𝗮𝗶𝗻𝗮𝗯𝗹𝗲 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗠𝗼𝗱𝗲𝗹𝘀! 🖥️📊 Complex machine learning models lack explainability, making it difficult to understand their inner workings and output. This is a significant hurdle in various cases, such as regulated industries where black box models are completely unacceptable. explainerdashboard is a Python library that helps you understand machine learning models, by offering a powerful interactive dashboard. Furthermore, the library supports various approaches, including SHAP values, permutation importances and dependence plots. Check the links below for more information, and make sure to follow me for regular data science content! 𝗲𝘅𝗽𝗹𝗮𝗶𝗻𝗲𝗿𝗱𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱 𝘄𝗲𝗯𝘀𝗶𝘁𝗲: https://lnkd.in/dfFkMGjH 𝗟𝗲𝗮𝗿𝗻 𝗠𝗟 𝗮𝗻𝗱 𝗧𝗦 𝗙𝗼𝗿𝗲𝗰𝗮𝘀𝘁𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗣𝘆𝗖𝗮𝗿𝗲𝘁📚: https://lnkd.in/dyByK4F #datascience #python #machinelearning #deeplearning #linkedin

𝗔 𝗣𝗼𝘄𝗲𝗿𝗳𝘂𝗹 𝗦𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝗮𝗹 𝗣𝗮𝗰𝗸𝗮𝗴𝗲 𝗳𝗼𝗿 𝗘𝘃𝗲𝗿𝘆𝗼𝗻𝗲! 💡 Are you looking for statistical software, but feel overwhelmed by the learning curve and cost of available options? JASP is an open source statistical package that includes numerous modules, while having a user friendly interface. JASP supports summary statistics, regression modeling, hypothesis testing, bayesian statistics and even machine learning! In the following example, we can see that fitting a logistic regression model with JASP is extremely easy. You can check the links below for more information, and make sure to follow me for regular content! 𝗝𝗔𝗦𝗣 𝗼𝗳𝗳𝗶𝗰𝗶𝗮𝗹 𝘄𝗲𝗯𝘀𝗶𝘁𝗲: https://jasp-stats.org/ 𝗟𝗲𝗮𝗿𝗻 𝗠𝗟 𝗮𝗻𝗱 𝗧𝗦 𝗙𝗼𝗿𝗲𝗰𝗮𝘀𝘁𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗣𝘆𝗖𝗮𝗿𝗲𝘁📚: https://lnkd.in/dyByK4F #datascience #statistics #machinelearning #deeplearning #linkedin

𝗚𝗲𝗼𝘀𝗽𝗮𝘁𝗶𝗮𝗹 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 𝘄𝗶𝘁𝗵 𝗚𝗲𝗼𝗣𝗮𝗻𝗱𝗮𝘀! 📊 GeoPandas is an awesome Python library for geospatial analysis and visualization. This library enhances the standard pandas dataframes, by adding support for geographic and other spatial information. Furthermore, the library includes various types of visualizations, such as choropleth plots. In the following example, we can see a choropleth plot of US drought severity, that has been created with GeoPandas. Have you ever used geospatial analysis in your projects? Check the links below for more information, and make sure to follow me for regular content! 𝗚𝗲𝗼𝗣𝗮𝗻𝗱𝗮𝘀 𝗼𝗳𝗳𝗶𝗰𝗶𝗮𝗹 𝘄𝗲𝗯𝘀𝗶𝘁𝗲: https://geopandas.org/ 𝗟𝗲𝗮𝗿𝗻 𝗠𝗟 𝗮𝗻𝗱 𝗧𝗦 𝗙𝗼𝗿𝗲𝗰𝗮𝘀𝘁𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗣𝘆𝗖𝗮𝗿𝗲𝘁📚: https://lnkd.in/dyByK4F #datascience #python #deeplearning #machinelearning #linkedin