
It’s one of the technique in which we implement KFold cross-validation, where k is equal to n i.e the number of observations in the data. Thus, every single point will be used in a validation set, we will create n models, for n-observations in the data. Each point/sample is used once as a test set while the remaining data/samples form the training set.

For almost a decade, Stack Overflow’s annual Developer Survey has been the largest survey of people who code around the world. This year they did a survey on 60,000+ software developers and shared some of the amazing statistics.
In this article, I’m going to write a detailed analysis of their survey result. So get ready to read some amazing analysis —
This network graph shows which technologies are most highly correlated with each other. The size of each circle corresponds to the proportion of survey respondents who use the technology tool.
Ruby and Rails tend to get used together. Similarly…

HackerEarth, with a community of around 4 million+ developers all around the world, is a highly sought after tech platform to hire quality developers. The coding problems on this platform are very exciting and challenging which can help you build a solid foundation on various topics like data structures and algorithms, data science and to say the least you can also participate in the different world class Hackathons. I have been crunching data for past few years and just two days back read this amazing survey that Hacker Earth has done where 16000 developers participated from 76 nations.
Below are…
I love Data. Period.
Like every day (30 minutes reading ritual before starting my office work), I was going through some great data science and machine learning articles to keep myself abreast of latest trends/info and I found a great survey that was done by HackerRank.
In this post, I’m going to cover the trends in the developers’ community in 2020. Let’s dive in!
The results indicate that Larger companies are more likely to want to hire specialists as compared to smaller companies (startups) which considers full-stack developers more important.

Recently I received an email from one of my readers asking me to write about Python’s complex topics such as Iterators, Generators, and Decorators. In this post, I’m going to cover the basics, implementation, and how to use them in your code.
An iterator is an object that can be iterated upon which means that you can traverse through all the values. List, tuples, dictionaries, and sets are all iterable objects.
To create an object as an iterator you have to implement the methods __iter__() and __next__() to your object where —
__iter__() returns the iterator object itself. …

In this post we will cover end to end Python Basics ( Part 1) that you should know.
Python is a high-level, most widely used multi-purpose, easy to read programming language.
It is —

Regular expression is a special sequence of characters that helps you match or find other strings or sets of strings using a pattern. In python, module named re isn used to work with RegEx.
[] : specifies a set of characters you wish to match
. : matches any single character
^ : checks if a string starts with a given character
+ : matches one or more occurrences of…

In python, a dictionary is a container that holds key-value pairs. Keys must be unique, immutable objects. If you try to access or modify keys that don’t exist in the dictionary, it raise a KeyError and break up your code execution. To tackle this issue, Python defaultdict type, a dictionary-like class is used

Programming Languages
Python

Dimensionality is the number of input variables or features for a dataset and dimensionality reduction is the process through which we reduce the number of input variables in a dataset. A lot of input features makes predictive modeling a more challenging task.
When dealing with high dimensional data, it is often useful to reduce the dimensionality by projecting the data to a lower dimensional subspace which captures the “essence” of the data. This is called dimensionality reduction.
~ Machine Learning: A Probabilistic Perspective, 2012.
There are various techniques for Dimensionality Reduction —
