Category: AI / Machine Learning / Deep Learning
-
The Four Pillars of a Successful Data Scientist: Logical Thinking, Hunger to Learn, Passion to Implement, and Communication Skills
In today’s data-driven world, the role of a data scientist is both crucial and multifaceted. Success in this field requires a blend of various skills and attributes. While technical proficiency and domain knowledge are important, four key elements stand out as the foundation for a successful data scientist: logical thinking, an insatiable hunger to learn…
-
Understanding the Proper and Best Practices for Using Generative AI
Generative AI, particularly large language models (LLMs) like OpenAI’s ChatGPT, has revolutionized the way we interact with technology, providing powerful tools for generating text, answering questions, and even creating art. However, many people harbor misconceptions about these tools, believing they can answer anything or solve every problem. As a data scientist, it’s crucial to understand…
-
Open Source Solutions for Comprehensive Data Governance and AI Governance
Introduction: As a data scientist with limited budget constraints, implementing effective data governance and AI governance practices can be challenging. However, leveraging open source solutions can provide cost-effective options for managing data, ensuring data lineage, and maintaining metadata integrity. In this article, we will explore step-by-step strategies and open source tools to establish a robust…
-
Fusing AI Canvas and BADIR: A Unified Approach to Transformative AI Projects
The BADIR (Business Question, Analysis Plan, Data Collection, Insights, and Recommendation) framework and the AI Canvas framework share some common principles as they both provide a structured approach to AI and data science projects. Let’s explore how they can work together: Alignment of BADIR and AI Canvas: Business Question: Both BADIR and AI Canvas…
-
Bookshelf for a Data Scientist
As a data scientist, reading book is a daily activity and most of my skills are built from reading. However, I am always reading different types of books outside the data science tools and technology. I would like to share some of the books recommended across different areas. Methodology When doing Data Science, many…
-
Different Jobs/Roles in a Data Science Team
People are always saying that Data Science is so hot and expected highly paid in the industry. There are lots of people trying to join in the industry. Everyone would like to become a data scientist. However, there are not many candidates really fit for the role as a data scientist. In this article, I…
-
Advanced Data Analytics with Free Tools
In the field of Data Science, there are lots of great tools without charging a penny. Data Analytic never requires software tools with high price and the analytic result should be the same either using SAS Data Miner or your own R code. As a data science consulting company, our teams are always using free…
-
Trends in Data Science for 2020 & 2021
I have not published any article for more than 2 months. It was extremely busy for the re-work on different project schedules and additional administrative work due to the coronavirus crisis. For this time, I would like to share an article planned to published by the end of January 2020. It’s about the coming trend…
-
AI Canvas to Work out AI
In this article, I would like to share the simple decision-making tool named AI Canvas and being used in MBA graduates at the university of Toronto’s Rotman School of Management, by professor Ajay Agrawal, University of Toronto. Before going into further details, it is vital to declare that AI / Data Science / Prediction…
-
Hardware Investment on Data Science in 2019/20
In this article, I would like to share some technical staff rather than high level data science topic for managers. There are more and more organizations investing in Machine Learning (mostly TensorFlow) including the installation and configuration of new servers and GPU for the intensive computations. Different hardware or cloud service will be discussed. Development…