Combating AI Fear
Fear of AI is a type of technophobia, which is a fear of computers, AI, robots, and similar technologies. AI has been the subject of much discussion and debate in…
Artificial Neural Networks
Big Data
Deep Neural Networks
Large Language Models(LLM)
Natural Language Processing
Tracking Recent LLM Model Announcements
Large Language Models have taken world by storm, open access to LLMs is needed by the humanity in order to take full advantage of these for development of cutting edge…
Tracking Advancements in Large Language Models(LLMs)
An LLM is a type of neural network based on the Transformer architecture, which was first introduced in a 2017 paper by Google engineers titled “Attention is All You Need.”…
Consumer GPUs for Deep Learning and LLM Projects: A Comprehensive Review
The article discusses the concepts of designing and building a custom GPU workstation for basic deep learning tasks such as training/fine-tuning LLMs. It highlights the importance of having CUDA and…
The Quest for AGI: Approaches and Benchmarks for Next-Level Artificial Intelligence
Achieving Artificial General Intelligence (AGI) is a complex and challenging task that requires significant advancements in several fields of research, including machine learning, computer science, neuroscience, psychology, and philosophy.
Exploring the Evolution of GPT: A Comparative Analysis of GPT-4, GPT-3, ChatGPT and Beyond
Introduction It is important to understand the difference between ChatGPT, ChatGPT Plus and GPT-3 because they use different variants of the same underlying language model, GPT (Generative Pre-trained Transformer). While…
ChatGPT is a Turning Point
Chatgpt is a turning point that impacts everyone many of us won't even understand why and how at the moment.
Creating a Development Environment using Docker
Introduction It is very important to have a local development and testing environment for developing data pipeline. Having a local development environment means you can try things and innovate with…
What is the Difference between Data Warehouse and a Data Lake ?
Data Lakes are the foundation for building AI driven solutions that many organizations need. There is much more information in audios, videos, images and social media chatter that can drive…
Using Windows Functions for Data Analysis in Greenplum
Windows functions are an important tool for data analysis. In this tutorial, we go through windows functions in SQL and provide examples for their use in Greenplum.
Optimizing Greenplum Data Warehouse Performance through Efficient Partitioning and Data Distribution
Introduction Greenplum follows a master/slave architecture, where data is distributed on segment nodes. Master node is responsible for executing user queries on segment nodes, and getting the results back to…
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.
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…
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…