Best of Data Science — January 2024

1. 1
   Article

   Medium·2y

   VScode Extensions for Documentation

   This post reviews the author's favorite VScode extensions for documentation, including Quarto, Jupyter, and Markdown All in One.

   391

   14
2. 2
   Article

   DEV·2y

   3 Terminal Commands to Increase Your Productivity

   Increase your productivity with these three terminal commands: creating aliases for commands, using pbcopy to copy file contents to the clipboard, and utilizing reverse search to find previously entered commands.

   300

   18
3. 3
   Article

   Medium·2y

   How to become an AI engineer (2024)

   AI engineering is a rapidly evolving field that involves developing and implementing AI systems. It requires programming skills, mathematical acumen, big data handling, algorithmic understanding, non-technical business skills, and analytical skills. To start a career in AI engineering, one needs to acquire these skills, pursue relevant education and certifications, network with other AI engineers, and apply for AI engineer jobs.

   117

   7
4. 4
   Article

   Medium·2y

   The Most Important Soft Skill in Tech

   Interviewing is the most important soft skill in tech. Building rapport, demonstrating value, and projecting professional growth are key objectives in an interview.

   52
5. 5
   Article

   Bits and Pieces·2y

   3 Ways To Detect Circular Dependencies In JavaScript Projects

   Discover three effective methods to detect and resolve circular dependencies in JavaScript projects: GitHub Actions, ESLint, and Bit.

   43
6. 6
   Article

   gitconnected·2y

   Mastering SQL Fundamentals

   This post provides a comprehensive guide to mastering SQL fundamentals, covering database terminology, relational models, applying SQL to real data, creating a new schema in MySQL, querying data using the SELECT statement, filtering data using the WHERE clause, ordering results using the ORDER BY clause, using logical and special operators, and understanding the importance of query efficiency. Mastery of SQL is emphasized as a valuable skill for data professionals.

   21

   1
7. 7
   Article

   KDnuggets·2y

   5 Super Helpful SQL Cheat Sheets You Can’t Miss!

   A collection of five super helpful SQL cheat sheets covering SQL basics, data preparation, joins, window functions, and interview questions.

   20
8. 8
   Article

   freeCodeCamp·2y

   What is a Hash Map? Time Complexity and Two Sum Example

   Learn about constant and linear time complexity, the use of hash maps, and how to solve the Two Sum problem using a hash table.

   19
9. 9
   Article

   Code Like A Girl·2y

   What is the difference between IaaS, PaaS and SaaS?

   Learn about the differences between IaaS, PaaS, and SaaS in cloud computing and their respective pros and cons.

   12
10. 10
    Article

    DEV·2y

    Modern Data Engineering RoadMap - 2024

    Data engineering is a fast-growing field with increasing demand. This article provides a roadmap for becoming a data engineer in 2024, covering the fundamentals, cloud computing, distributed frameworks, data warehouses, real-time data processing, NoSQL databases, and workflow orchestration tools. It also highlights the importance of upgrading from ETL to ELT, cloud dominance, the rise of real-time data processing, and automation and democratization in data engineering.

    13
11. 11
    Article

    Medium·2y

    Important Python Topics for Data Engineering

    Learn the important Python topics for data engineering, including variables, data types, operators, if statements, loops, functions, modules, exception handling, lists, tuples, sets, dictionaries, strings, arrays, file handling, and working with different file formats.

    12

    1
12. 12
    Article

    Towards AI·2y

    The Unsung Hero of Machine Learning — Linear Algebra

    Linear algebra is an essential component of machine learning, data mining, deep learning, and optimization algorithms. Gaussian elimination is used in various applications, such as solving optimization problems and finding best-fit parameters. The concepts of linear dependence and independence are also important in understanding linear equations and systems. Overall, understanding linear algebra is crucial for making informed decisions based on quantitative data.

    11
13. 13
    Article

    KDnuggets·2y

    SQL Group By and Partition By Scenarios: When and How to Combine Data in Data Science

    Learn about the scenarios and techniques of grouping and aggregating data, as well as partitioning and ranking data in SQL.

    10