Bite Sized Learning: Printing Patterns

Bite Sized Learning - Prining Patterns

This will be handy when you attend interviews or exams

Refer the code file for various patterns using numbers, alphabets and characters - Patterns

Comments

Post a Comment

Popular posts from this blog

Bite Sized Learning: Data Preparation

Image
  Importance of Data Preparation & Common Methods   Data preparation is the various methods and steps taken to transform the data such that it is suitable for ML algorithms. Here quality precedes over quantity. Hence it is essential to transform the raw data into to a more informative format for a better modelling task. Below are the most commonly followed data preparation tasks in data science industry   Data Cleaning Feature Engineering Data Transformation Feature Extraction   Data Cleaning: Data cleaning is the process of detecting and also treating inaccurate data points from a data set. This is the most time consuming and critical part of ML. It simply goes "garbage in = garbage out". Below are some of the methods to clean data Find the number / percentage (both) of missing rows or null values (NAN) & treat it Identify the duplicate rows within the dataset & treat it Detect the outliers using statistics & treat it using doma...
Read more