Ace the Data Science Interview by Refreshing Top Hadoop Questions and Answers
In this article, we discuss key concepts of hadoop and answer various common questions related to hadoop.
Greenplum Database Programming with SQLAlChemy Library
This tutorial provides, hands on coding examples covering database programming for Greenplum/PostgreSQL using SQLAlChemy library.
Step by Step Greenplum Database Programming Tutorial Using Python
This tutorial shares basic database programming code for PostgreSQL and Greenplum using Python and psycopg2 library.
Getting Started with MADlib for Greenplum Data Warehouse
Not many data scientists realize that it is possible and much more beneficial to build data science models directly on top of a data warehouse. Apache MADlib is an open-source…
Greenplum Getting Started | Hands-On Tutorial
Greenplum getting started tutorial, covering basic commands to start/stop the database, creating schema, and tables.
10 Key Concepts and Ideas to Apply When Solving Any Data Science (Machine Learning) Problem ?
Solving data science problems requires systematic thinking and approach, here's some of the key concepts and steps that you need to apply when trying to solve data science problems.
Modern Big Data Engineering Architecture and Big Data Pipelines
Understanding big data architecture, and developing effective strategies for big data is key to building modern data science solutions. Here, we provide high level overview of big data architecture.
Top Clustering Questions for Acing the Data Science Interview (Clustering MCQs)
Q1. What is the minimum no. of variables/ features required to perform clustering? A. 0 B. 1 C. 2 D. 3 Solution: (B) At least a single variable is required…
Python Multiple Choice Questions with Answers(Python MCQs)
Python multiple choice questions for learning and self improvement.
Ace the Data Science Interview by Preparing for the Most Common Questions for Machine Learning and Data Science
Common data science questions and answers for refreshing your data science knowledge with the help of most common data science interview questions.
Data Science versus Business Intelligence ? What Do You Need ?
Building great data science models is key to success in business. Understanding the difference between data science and business intelligence is key to using these to succeed in your business…
Apache Spark Tutorial Covering Concepts, Questions and Answers
Spark is a fast, easy-to-use and flexible data processing framework. It has an advanced execution engine supporting cyclic data flow and in-memory computing. Spark can run on Hadoop, standalone or…
Sentiment Analysis Using Opinion Tagging Approach for Important Business Use Cases
What is Sentiment Analysis ? Sentiment analysis and opinion mining technology is an important tool for businesses, and governments to judge and evaluate the reaction of people for their services.…
Why do we need GPU’s for Deep Learning ?
Deep learning is a field with intense computational requirements, and your choice of GPU will fundamentally determine your deep learning experience. As discussed previously a CPU is divided into multiple…
Deep Dive into understanding and making best use of Open Source Greenplum Data Warehouse Architecture
Greenplum Architecture The main reason behind adaptation of massively parallel processing(MPP), data warehouse(DWH) solution is MPP architectural principles. These principles aim at removing main drawbacks of traditional DWH, and make…
Learning Exploratory Data Analysis Using Redwine Dataset
Exploratory data analysis is an important step in any data science and even business intelligence project, which gives you adequate understanding of underlying data.
Introduction to Database Programming in Python with SQLAlchemy Library
Database programming in Python using SQLAlchemy library that provides uniform interface for connecting with different databases.
Exploratory Data Analysis and Visualization Using Seaborn Library
This article provides a good overview of exploratory data analysis techniques, and then provides code examples using seaborn library.
Understanding Greenplum Architecture and Application for Data Science and Business Intelligence Use Cases
Understanding Greenplum architecture and use cases for various big data and data science scenarios for business and industry.
Understanding Payment Fraud Prediction as a Data Science Problem Involving Payment Big Data
Understanding payment fraud is key to successfully building a payment fraud detection system. In this article, we provide a comprehensive overview of payment fraud analysis.