#### How To Update Your Beliefs Systematically – Bayes’ Theorem

Here’s a great video that explains Bayes’ theorem with examples and implications for life. I didn’t say it explicitly in the video, but in my view the Bayesian trap is interpreting events that happen repeatedly as events that happen inevitably. They may be inevitable OR they may simply be the outcome of a series of […]

Read More#### Statistics and Probability for Data Science

- Frank
- June 8, 2022
- data science edureka
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A lot of people ask me about breaking into the fields of AI and data science. Many are surprised to hear that the core of it all revolves around statistics more so than “just code.” This session on Statistics And Probability will cover all the fundamentals of stats and probability. Topics Covered : 00:00:00 Introduction […]

Read More#### Practical Statistics for Data Scientists – Exploratory Data Analysis

This is an overview of Chapter 1 of Practical Statistics for Data Scientists. Shashank Kalanithi goes over the first couple of chapters of this book because the later chapters cover similar materials from my Hands on Machine Learning book overview videos.

Read More#### Machine Learning for Beginners: Binary Cross Entropy Loss Error Function

- Frank
- June 26, 2021
- AI
- ai for beginners
- artificial intelligence
- artificial intelligence for beginners
- binary
- binary cross entropy
- binary log loss
- cost
- cost function
- cross entropy
- cross entropy loss
- Data Science
- error function
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- input
- label
- log loss
- logarithm
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- Machine Learning
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- Math
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- mean
- ML
- Perceptron
- Prediction
- Python
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- Statistics
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In this lesson from Python Simplified learn the binary Log Loss/Cross Entropy Error Function and break it down to the very basic details.

Read More#### A Clear Explanation of Naive Bayes

StatQuest with Josh Starmer explains Naive Bayes in a clear way. When most people want to learn about Naive Bayes, they want to learn about the Multinomial Naive Bayes Classifier – which sounds really fancy, but is actually quite simple. This video walks you through it one step at a time and by the end, […]

Read More#### Bayesian Data Science by Simulation Tutorial

Here’s an interesting session from the SciPy 2020 virtual conference. As a foundational tutorial in statistics and Bayesian inference, the intended audience is Pythonistas who are interested in gaining a foundational knowledge of probability theory and the basics of parameter estimation. Knowledge of `numpy`, `matplotlib`, and Python are prerequisites for this tutorial, in addition to […]

Read More#### This Is How Easy It Is to Lie With Statistics

- Frank
- April 6, 2020
- applications of mathematics
- applications of statistics
- applied math
- applied statistics
- how statistics can mislead
- how to lie with statistics
- major prep
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- misleading statistics
- real world use of statistics
- Statistics
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- the power of statistics

Zach Star explains how misleading statistics can be (even when the numbers are 100% correct!).

Read More#### Extreme Events and How to Live with Them by Nassim Nicholas Taleb

Darwin College Lecture Series hosts Professor Nassim Nicholas Taleb to talk about the impact of extreme events. While COVID is not directly referenced, it’s clear that the current pandemic counts as an extreme event. Nassim Nicholas Taleb spent 21 years as a risk taker before becoming a researcher in philosophical, mathematical and (mostly) practical problems […]

Read More#### Coronavirus: Keep calm and know the data

- Frank
- March 16, 2020
- coronavirus
- coronavirus china
- coronavirus crisis
- coronavirus data
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- crisis
- Data
- disease
- evening standard
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- London
- news
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- pandemic
- standard
- Statistics
- UK

Coronavirus was declared a pandemic on Wednesday due to its widespread transmission across the world. But in terms of severity, it remains relatively low, with certain demographics more vulnerable than others. Evening Standard shows us five categories of data to shed some perspective on the scale of the crisis.

Read More#### Michael I. Jordan on Machine Learning, Recommender Systems, and the Future of AI

Lex Fridman interviews Michael Jordan – not that Michael Jordan. Michael I Jordan is a professor at Berkeley, and one of the most influential people in the history of machine learning, statistics, and artificial intelligence. He has been cited over 170,000 times and has mentored many of the world-class researchers defining the field of AI […]

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