Objective, Inc.’s Post

Can My Sorting Algorithm Beat Quick Sort? Some time ago, I devised a sorting algorithm inspired by quicksort and selection sort, naming it BE Sort for Beginning End Sort. To comprehend it better, please check out the GitHub repository. Today, in an attempt to evaluate its performance against quicksort, it performed unfavorably. The time taken to sort 100, 1000, and 10000 elements is as follows: For 100: BE Sort (0.000036), Quick Sort (0.000013) For 1000: BE Sort (0.003786), Quick Sort (0.000151) For 10000: BE Sort (0.322454), Quick Sort (0.002342) Despite its suboptimal performance, this experience has offered valuable insights into algorithmic thinking. I recognize that I heavily utilized nested loops, and the algorithm lacks optimization. It comprises a two-stage process, and each stage is time-consuming. Although it did not surpass quicksort, it has ignited ideas for optimization and exploring alternative solutions. GitHub Repository: https://lnkd.in/ga8ZhyCH

This week in bootcamp we are learning how to use FastAPI to build APIs and access and manipulate data in those APIs. I am really enjoying learning about data management and can't wait to refactor my past projects to include FastAPI. https://lnkd.in/gerYqX9f

Today we’re shipping Tinybird Charts 📊 the fastest way to build visualizations over your real-time data. With just a few clicks, you can build fast charts, even faster. Already with Tinybird, you’ve been able to ingest data from anywhere with just a few clicks (or a single command-line instruction). From there, you can build Pipes using SQL, a language you already know. And then, you can turn any Pipe into a high-concurrency, low-latency REST API. Now, you can turn any Pipe into a Tinybird Chart 🚀 Read more about Tinybird Charts and get started with Tinybird today. 👉 https://lnkd.in/e3p-czYQ

👩🎓 You can learn a lot from user queries! From understanding what users are searching for to enhancing your dataset, observability is key to improving your application over time. 📚 Here's a short guide on how to do so with Metal’s list queries API.

GraphBolt v0.6.0 is out with one of the most requested features 🚀 You can now use the visual query builder to create and edit your queries, mutations, and subscriptions by exploring your GraphQL schema. Tip: Hover over an argument or field to get its documentation. https://lnkd.in/emEFAtev

I contemplated on and then wrote up my own custom decision tree algorithm code: https://lnkd.in/gMUhkUDP I got the idea from bifurcation. A decision tree normally finds the best split that maximizes the information criterion at each split, but I decided to follow similar thinking, but use measures of central tendency (the mean) and split on a decision (field) that brings the greatest reduction in error residual. Resulted in a nice balanced tree with a surprisingly low error. 22 final clusters (based on n of 10 splits) from 50 records

TidyMass is a comprehensive computational framework for data processing and analysis of LC-MS data using tidyverse principles. #rstats

I used @supabase to make the editing live between the users in the real time

Three weeks ago I rotated my second monitor to a vertical position, only to revert it back to horizontal today. Here's what I discovered: Vertical Pros: Ideal for reading long documents, coding and looking at long vertical tables (which you shouldn't ever do - just make a Pivot Table). Must be convenient for lawyers, programmers, data scientists. Vertical Cons: Wider summary tables and presentations, staples of management, become tough to view - appearing tiny at the top, leading to discomfort in your neck because you have to often look up. Compatibility: Many apps are not "comfortable" in vertical setup, resulting in overlapping buttons and distorted text. Flexibility Is Key: Switching between orientations is straightforward and can significantly benefit specific tasks. The only limitation is cable length; keep some slack in your cables, and flipping your monitor becomes very simple. This experiment underscored the importance of adaptability and the need to tailor our tools to suit our immediate needs, despite the occasional logistical hurdle.

🍏 Want to get started with building Multi-modal applications? https://lnkd.in/dz6my89p 💪 This practical guide by Kaushal Kumar Choudhary takes you through building 3 applications using CLIP multi-modal model and LanceDB (YC W22) as vector store, allowing you to query via embeddings, keywords and even SQL! It covers - Multi-Modal Search using CLIP - Turning that into Gradio application - Multi-Modal Video Search 📓 All of them also come with a working colab notebook that you can follow along. 🎉 Find more such projects with hands on code here - https://lnkd.in/dpRydE6y