Probabilistic Programming allows to define probabilistic models and develop Bayesian inferences. It can be used to make decisions in the face of uncertainty. Probabilistic reasoning has been used widely in most AI systems of do complex tasks such as predicting stock prices, recommender systems, diagnosing systems, detecting cyber intrusions and image detection.

PyMC3 is a new open source Probabilistic Programming framework written in Python. Providing recent advances in Markov chain Monte Carlo (MCMC) sampling, PyMC3 allows inference on increasingly complex models. PyMC3 features next-generation Markov chain Monte Carlo (MCMC) sampling algorithms such as the No-U-Turn Sampler [1], a self-tuning variant…

Survival analysis is a statistical method for predicting the expected duration of time until certain events happen. Such events could be death, removal, churn, damage, failure, redemption, expiration, etc. The most common parameter in all these event is time which is the prominent part of any survival analysis. Survival analysis always try to measure probability, detect portion of population or evaluate effect of particular circumstances on survival over the event at certain time. This post try to cover most important details, mathematical intuition and theories, and whole process for survival curves and survival regressions.

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LIFELINES: Survival Analysis in Python


I recently started to read a book “Effective Python” and I want to summarize what I learn from this book in these series of stories. First step is to study the best way to do most common things in Python which we can call it the way of Pythonic Thinking. Here is 12 steps to follow this particular style while you are programming Python.

1: Know your Python

Pythonic is an adjective that describes an approach to computer programming that agrees with the founding philosophy of the Python programming language. There are many ways to accomplish the same task in…

Photo from: Artificial intelligence detects a new class of mutations behind autism (Princeton University)

Query Amazon Redshift Data Using Python (Pandas and NumPy)

Amazon Redshift data warehouse is part of the cloud-computing platform Amazon Web Services (AWS). Redshift name suggests a shift from Oracle. AWS is an efficient solution to collect and store all data of organizations and analyze them using various business intelligence tools. Python is widely used and is a most favorite tool in Data Science and Machine Learning community along being a flexible and open source language.

In this post, accessing your amazon redshift data using Python is reviewed. One easy way to access your data with python is using Pandas library. But one issue with this library may be…

Reza Rashetnia, PhD

Data Scientist @ Knowbe4

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