- A Concise Course in Statistical Inference: The Free eBook [Silver Blog]
Check out this freely available book, All of Statistics: A Concise Course in Statistical Inference, and learn the probability and statistics needed for success in data science.
- Should Data Scientists Model COVID19 and other Biological Events [Silver Blog]
Biostatisticians use statistical techniques that your current everyday data scientists have probably never heard of. This is a great example where lack of domain knowledge exposes you as someone that does not know what they are doing and are merely hopping on a trend.
- 5 Statistical Traps Data Scientists Should Avoid [Gold Blog]
Here are five statistical fallacies — data traps — which data scientists should be aware of and definitely avoid.
- How to Become a (Good) Data Scientist – Beginner Guide [Platinum Blog]
A guide covering the things you should learn to become a data scientist, including the basics of business intelligence, statistics, programming, and machine learning.
- 6 bits of advice for Data Scientists [Silver Blog]
As a data scientist, you can get lost in your daily dives into the data. Consider this advice to be certain to follow in your work for being diligent and more impactful for your organization.
- Which Data Science Skills are core and which are hot/emerging ones? [Gold Blog]
We identify two main groups of Data Science skills: A: 13 core, stable skills that most respondents have and B: a group of hot, emerging skills that most do not have (yet) but want to add. See our detailed analysis.
- Statistical Modelling vs Machine Learning [Silver Blog]
At times it may seem Machine Learning can be done these days without a sound statistical background but those people are not really understanding the different nuances. Code written to make it easier does not negate the need for an in-depth understanding of the problem.
- 5 Useful Statistics Data Scientists Need to Know [Gold Blog]
A data scientist should know how to effectively use statistics to gain insights from data. Here are five useful and practical statistical concepts that every data scientist must know.
- Top 10 Statistics Mistakes Made by Data Scientists [Silver Blog]
The following are some of the most common statistics mistakes made by data scientists. Check this list often to make sure you are not making any of these while applying statistics to data science.
- How to correctly select a sample from a huge dataset in machine learning [Silver Blog]
We explain how choosing a small, representative dataset from a large population can improve model training reliability.
- The Essential Data Science Venn Diagram [Gold Blog]
A deeper examination of the interdisciplinary interplay involved in data science, focusing on automation, validity and intuition.
- Introduction to Statistics for Data Science [Gold Blog]
This tutorial helps explain the central limit theorem, covering populations and samples, sampling distribution, intuition, and contains a useful video so you can continue your learning.
- The 5 Basic Statistics Concepts Data Scientists Need to Know [Silver Blog]
Today, we’re going to look at 5 basic statistics concepts that data scientists need to know and how they can be applied most effectively!
- Machine Learning Cheat Sheets [Platinum Blog]
Check out this collection of machine learning concept cheat sheets based on Stanord CS 229 material, including supervised and unsupervised learning, neural networks, tips & tricks, probability & stats, and algebra & calculus.
- Essential Math for Data Science: ‘Why’ and ‘How’ [Platinum Blog]
It always pays to know the machinery under the hood (even at a high level) than being just the guy behind the wheel with no knowledge about the car.
- Basic Statistics in Python: Descriptive Statistics [Gold Blog]
This article covers defining statistics, descriptive statistics, measures of central tendency, and measures of spread. This article assumes no prior knowledge of statistics, but does require at least a general knowledge of Python.
- Causation in a Nutshell [Gold Blog]
Every move we make, every breath we take, and every heartbeat is an effect that is caused. Even apparent randomness may just be something we cannot explain.
- Explaining the 68-95-99.7 rule for a Normal Distribution [Silver Blog]
This post explains how those numbers were derived in the hope that they can be more interpretable for your future endeavors.
- Football World Cup 2018 Predictions: Germany vs Brazil in the final, and more [Gold Blog]
Looking ahead to the FIFA World Cup that kicks off this month (14th June), we have created the official KDnuggets predictions.
- Key Algorithms and Statistical Models for Aspiring Data Scientists [Gold Blog]
This article provides a summary of key algorithms and statistical techniques commonly used in industry, along with a short resource related to these techniques.
- The 10 Statistical Techniques Data Scientists Need to Master [Gold Blog]
The author presents 10 statistical techniques which a data scientist needs to master. Build up your toolbox of data science tools by having a look at this great overview post.