Machine learning classification
Introduction Supervised machine learning has two types: 1) Regression, 2) Classification In regression, we already saw that it deals with the continuous data type that [continue reading..]
Articles by Mitra N Mishra
LinkedList in Python
Introduction Linked List is also similar to an array is a linear data structure but dissimilar in the manner of it doesn’t use contiguous memory location, [continue reading..]
Array in Python
Introduction In this article, we will learn about Array. data structure is a very important subject in computer science. Data structure is a particular way [continue reading..]
Why Becoming a Data Scientist is the Next Logical Move?
Amongst the different job profiles, the Data scientist is most lucrative and very trending job profile these days. Companies hiring data scientists to handle their [continue reading..]
Apache Hive
Introduction Hive is developed on top of Hadoop. It is a data warehouse framework for querying and analysis of data that is stored in HDFS. [continue reading..]
Hadoop Architecture
Architecture overview Hadoop has three core components, plus ZooKeeper if you want to enable high availability: Hadoop Distributed File System (HDFS) MapReduce Yet Another Resource [continue reading..]
Common machine learning algorithms for beginners
Introduction Machine learning is one of the hottest trendings in tech industries today. Machine learning is very powerful to make prediction or recommendations based on huge [continue reading..]
Mathematics for data science: Linear Algebra Part-1
Introduction Linear algebra is the bedrock of data science and machine learning. Linear algebra provides mathematical insights to solve equations we use to build models. [continue reading..]
An introduction to data science
Introduction What motivates people to get into data science fields? Why do people want to become a data scientist? Actually, if you want to find [continue reading..]
Artificial Neural Network( The basic idea behind machine’s brain)
“Machine learning involves in adaptive mechanisms that enable computers to learn from experience, learn by examples and learn by analogy. Learning capabilities can improve the [continue reading..]