originally posted by the author on Linkedin : Link It is very tempting for data science practitioners to opt for the best known algorithms for a given problem.However...
Finding the quality of a tennis player by calibrating and analyzing the aces notched up by tennis players or predicting the next Pele or Cristiano Ronaldo after training ...
Summary: Continuing from out last article, we searched the web to find all of the most common myths and misconceptions about Big Data. There were a lot more than we t...
One of most excruciating pain points during Data Exploration and Preparation stage of an Analytics project are missing values. How do you deal with missing values –...
For a service provider, being able to anticipate its customer’s behaviour has three major benefits. It can generate customer delight, prevent customer exhaustion, a...
Summary: It’s become almost part of our culture to believe that more data, particularly Big Data quantities of data will result in better models and therefore better ...
For almost as long as we have been writing, we’ve been putting meaning into maps, charts, and graphs. Some 1,300 years ago, Chinese astronomers recorded the position of...
The Riemann Hypothesis is arguably the most important unsolved problem in mathematics. It falls into an area called Analytic Number Theory which is essentially number the...
The books listed at the top are more recent and show the evolution (one might say the come back) of data science towards deep learning and AI. The books in the other half...
Summary: There is a common misconception that data is the enemy of intuition. It’s true that sometimes our clients are misled by their preconceived notions. But all...
We are in the process of writing and adding new material (compact eBooks) exclusively available to our members, and written in simple English, by world leading experts in AI, data science, and machine learning.