Feeling impressed to jot down your first TDS submit? We’re always open to contributions from new authors.
Our most-read and -discussed articles from the previous month recommend that neither excessive summer time climate nor world sporting occasions can derail our readers from upping their abilities and increasing their data of rising matters.
Our month-to-month highlights cowl information science profession paths, cutting-edge LLM workflows, and always-relevant matters round SQL and Python. They’re delivered to you with our authors’ signature mix of accessibility and experience, so in case you missed any of them, we hope you take pleasure in our July must-reads. (If sizzling temperatures are affecting your consideration span—we all know the sensation!—you’ll be glad to know that each one however two of the articles under are under-10-minute reads.)
Month-to-month Highlights
- Mastering SQL Optimization: From Functional to Efficient Queries
Who may ever refuse main time financial savings when working your queries? Yu Dong’s sensible information to SQL optimization made a splash by providing six superior suggestions which have helped her cut back question working time by 50 hours day by day at her current job; they’re particularly related for information professionals working in Snowflake SQL. - Full Guide to Building a Professional Portfolio with Python, Markdown, Git, and GitHub Pages
Clear, fast, and filled with useful code snippets, Pierre-Etienne Toulemonde’s debut TDS article grew to become a success by strolling readers via the method of constructing a top-notch skilled portfolio that meets two key standards: a free resolution, and minimal configuration. - Running Local LLMs is More Useful and Easier Than You Think
As using LLMs spreads wider and deeper into our day by day workflows, so does the necessity to run these highly effective fashions domestically. Guillaume Weingertner shared a concise, step-by-step information that demonstrated how that is not a posh, resource-intensive course of.
- Evolution of Data Science: New Age Skills for the Modern End-to-End Data Scientist
“What has dramatically modified, nonetheless, are enterprise expectations, the know-how panorama and the increasing vary of abilities an information scientist is anticipated to have.” Col Jung took us on a journey via the historical past of information science and outlined the kinds of abilities practitioners have to grasp to remain aggressive at this time. - Leading by Doing: Lessons Learned as a Data Science Manager and Why I’m Opting for a Return to an Individual Contributor Role
Profitable information science careers don’t depend upon particular titles or org-chart positions; as Dasha Herrmannova, Ph.D. argues in a considerate reflection on her personal current profession strikes, probably the most important ingredient in success is knowing your individual priorities and discovering a task that matches them, not the opposite manner round. - Document Parsing Using Large Language Models — With Code
We had been thrilled to welcome again Zoumana Keita’s work this month—particularly when the article in query was a affected person, easy-to-follow tutorial on a promising entrance for LLM adoption: doc parsing (on this case, PDF recordsdata of scientific analysis papers). - Implementing Neural Networks in TensorFlow (and PyTorch)
Rounding out our month-to-month highlights is Shreya Rao’s newest addition to her Deep Studying Illustrated sequence: a practical-implementation information for anybody who’d like to achieve hands-on expertise with the theoretical ideas Shreya launched in earlier articles. Observe alongside to learn to construct neural networks in TensorFlow (with a bonus PyTorch part, too!).
Our newest cohort of recent authors
Each month, we’re thrilled to see a contemporary group of authors be a part of TDS, every sharing their very own distinctive voice, data, and expertise with our group. Should you’re searching for new writers to discover and comply with, simply browse the work of our newest additions, together with Jason Zhong, Don Robert Stimpson, Nicholas DiSalvo, Rudra Sinha, Harys Dalvi, Blake Norrish, Nathan Bos, Ph.D., Ashish Abraham, Jignesh Patel, Shreya Shukla, Vinícius Hector, Fima Furman, Kaizad Wadia, Tomas Jancovic (It's AI Thomas), Laurin Heilmeyer, Li Yin, Kunal Kambo Puri, Mourjo Sen, Rahul Vir, Meghan Heintz, Dron Mongia, Mahsa Ebrahimian, Pierre-Etienne Toulemonde, Shashank Sharma, Anders Ohrn, Alex Davis, Badr Alabsi, PhD, Jubayer Hossain Ahad, Adesh Nalpet Adimurthy, Mariusz Kujawski, Arieda Muço, Sachin Khandewal, Cai Parry-Jones, Martin Jurran, Alicja Dobrzeniecka, Anna Gordun Peiro, Robert Etter, Christabelle Santos, Sachin Hosmani, and Jiayan Yin.
Thanks for supporting the work of our authors! We love publishing articles from new authors, so for those who’ve just lately written an fascinating venture walkthrough, tutorial, or theoretical reflection on any of our core matters, don’t hesitate to share it with us.
Till the subsequent Variable,
TDS Group
SQL Optimization, Data Science Portfolios, and Other July Must-Reads was initially printed in Towards Data Science on Medium, the place persons are persevering with the dialog by highlighting and responding to this story.