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Probability theory is a fundamental concept in statistics, data science, and machine learning. It's the mathematical framework that allows us to quantify uncertainty and make informed decisions based on data. By understanding probability, we can predict outcomes, assess risks,

Foundations of ML:

Está cordialmente invitado a regresar al Ecuador, para que compruebe a dónde van a parar los verdaderos corruptos. El hospedaje está asegurado. Le adjunto una foto del avance de la cárcel que construimos pensando en su comodidad.

Data science, a multidisciplinary field, plays a crucial role in extracting valuable insights from data to drive informed decision-making and enhance business strategies. pyoflife.com/data-science-i… #DataScience #machinelearning #ArtificialInteligence #datavisualizations #datasets

Probability and Measure by K. R. Parthasarathy

ML Foundations:

ML and Computing:

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Saber comunicar es posiblemente una de las habilidades más importantes de un data scientist. Me encanta este libro porque justamente estructura las fallas más comunes al momento de comunicar resultados y, sobre todo, nos ayuda a entender cómo evitarlas. He visto a muchos

Machine Learning. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Books #Programming #Coding #100DaysofCode geni.us/ML-Course

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1/ Most biologists fail at computation not because it’s hard— but because they start in the wrong place. Here’s the roadmap I wish I had 12 years ago.

Understanding Statistics:

Drawing a Biplot of a Principal Component Analysis (PCA) can be a powerful way to visualize your data. Here’s a detailed guide on the essentials: ✔️ PCA Explained: Principal Component Analysis (PCA) helps in reducing the dimensionality of data sets while preserving as much