aspashur retweeted
When you have a whole bunch of raw data, it's often hard to make sense of without visuals.
So in this guide, Nikhil takes you through analyzing a dataset and creating six different visualizations for it.
You'll learn about heatmaps, EPS scatters, return violins, and more, along with the insights they can give you.
freecodecamp.org/news/financโฆ
aspashur retweeted
A vector database stores data as lists of numbers called embeddings, which lets it search by meaning.
And it's what powers many recommendation systems, RAG apps, and AI agents.
In this course, you'll learn how they work, from the math to a working semantic search project.
freecodecamp.org/news/learn-โฆ
aspashur retweeted
Thinking Clearly with Data โ Guide to Quantitative Reasoning and Analysis: link.amazon/B0bLHiDpo
Amazon Summary:
โข Ideal textbook for introductory quantitative methods courses in data science, statistics, political science, economics, psychology, sociology, public policy, and other fields
โข Introduces the basic toolkit of data analysisโincluding sampling, hypothesis testing, Bayesian inference, regression, experiments, instrumental variables, differences in differences, and regression discontinuity
โข Uses real-world examples and data from a wide variety of subjects
โข Includes practice questions and data exercises
aspashur retweeted
If you want to defend against attackers, you have to understand how they attack.
And you can learn how to break into systems (ethically and responsibly) in this course.
You'll learn about target reconnaissance, vulnerability assessment, web exploitation, and more using a dedicated Capture the Flag machine.
freecodecamp.org/news/learn-โฆ
aspashur retweeted
Your notes, PDFs, and docs are hard to search once they pile up in folders.
In this tutorial, Darsh teaches you how to build a private RAG Q&A agent that runs on your own machine.
You'll use Python, LangChain v1, Ollama, Qwen, and ChromaDB to query your documents and get answers with cited sources.
freecodecamp.org/news/build-โฆ
aspashur retweeted
If you need to brush up your math skills, this collection of courses is for you.
It's a list of more than 220 of the top online math courses from the 60 best universities in the world.
You can learn about linear algebra, differential equations, vector calculus, statistics and probability, and lots more.
freecodecamp.org/news/math-oโฆ
aspashur retweeted
If you want to learn how to build and deploy ML models, this course is for you.
It covers Exploratory Data Analysis, Feature Engineering, Model Validation, & MLOps integration.
By the end you'll be able to manage complex data projects & deploy your models.
freecodecamp.org/news/end-toโฆ
aspashur retweeted
If you're building a project and eventually hope to bring others on board, you'll want to create a README file.
And in this guide, @casweb_dev explains how to structure it effectively.
He walks you through all the important info to include, and even shares a template you can use for your own READMEs.
freecodecamp.org/news/how-toโฆ
aspashur retweeted
๐๐๐จ๐ฌ๐ฉ๐๐ญ๐ข๐๐ฅ ๐๐๐ญ๐ ๐๐๐ข๐๐ง๐๐ ๐๐จ๐ซ ๐๐ซ๐๐๐ง ๐๐ฅ๐๐ง๐ง๐ข๐ง๐
A curated collection of dozens of research papers on the urban planning applications of geospatial data science: covering urban networks, polycentricity, walkability, mobility, inequality, digital twins, heat islands, resilience, 15-minute cities, and more.
From OSMnx and road network scaling to mobility-driven inequality, urban biodiversity, digital urban twins, and global 3D building datasets - this collection shows how spatial data and network science are reshaping how we understand and design cities.
My tutorials: youtube.com/@milanjanosov
A taste of the list:
1. Modeling and Analyzing Urban Networks and Amenities with OSMnx
zurl.co/Dulv2
2. The Coherence of US Cities
zurl.co/ovUAC
3. Data-Driven Approach to Estimate Urban Heat Island Impacts on Building Energy Consumption
zurl.co/CWr8O
4. Urban Highways Are Barriers to Social Ties
pnas.org/doi/10.1073/pnas.24โฆ
5. Uncover the Nature of Overlapping Community in Cities
zurl.co/MFNQt
6. A Universal Framework for Inclusive 15-Minute Cities
zurl.co/6prYu
๐
๐ฎ๐ฅ๐ฅ ๐ฅ๐ข๐ฌ๐ญ: open.substack.com/pub/milanjโฆ
๐๐ก๐ ๐๐๐ฐ ๐๐๐ข๐๐ง๐๐ ๐จ๐ ๐๐๐ฉ๐ฌ - thenewscienceofmaps.com/
aspashur retweeted
A web service is a standardized way for software apps to communicate with each other over a network.
And in this tutorial, Kumar teaches you how they work and why they're important.
You'll learn about two main types of web services (SOAP and REST) and when to use each one in your projects.
freecodecamp.org/news/how-weโฆ
aspashur retweeted
Not everyone who works with geospatial data wants to work in a terminal. Now terrio has a UI for them.
Run one command and a page opens in your browser, with a form for every terrio command:
terrio ui
Choose a command, fill in the options, pick your files and click Run. Converting formats, reprojecting rasters, clipping vectors and the rest of terrio's tools are all there, with no command line to memorize.
What you get
- A form for every command: all 150 commands and subcommands. The forms are generated from terrio's own command catalog, so they always match the version you have installed.
- Command search: find a tool by name instead of scrolling through the list.
- A file browser: pick inputs and outputs from your computer's disk.
- The equivalent command line: copy it into a script when you are ready to automate, or use it to learn the CLI.
- Cancel: stop a long-running command with one click.
- Nothing extra to install: the UI ships inside terrio, and the page loads nothing from the internet, so it works offline.
- Local by default: the server listens only on your own computer and every request needs a random session token.
terrio reads, writes, converts and reprojects geospatial rasters, vectors and point clouds in pure Rust, with no GDAL installation needed. Its commands and options follow GDAL's, many of its algorithms and drivers are ports of GDAL, PROJ and PDAL code, and its results are tested against them. If terrio is useful to you, please consider sponsoring GDAL: gdal.org/en/stable/sponsors/โฆ
Try it out
- Documentation: terrio.dev
- GitHub: github.com/opengeos/terrio
#GIS #Rust #OpenSource #Geospatial #Python #GDAL
aspashur retweeted
Web research agents don't have to depend on hosted chat tools.
In this tutorial, Darsh shows you how to build a personal AI research agent with Ollama, Qwen, and Python.
Your agent will search the web, fetch pages, summarize results locally, and save a Markdown digest on your machine.
freecodecamp.org/news/build-โฆ
aspashur retweeted
As a software developer, you should know how to work with databases.
And if you need to learn the basics or brush up on your skills, this course is for you.
It covers client & network layers, execution management, storage engines, indexing, & lots more.
freecodecamp.org/news/learn-โฆ
MicroPython Embedded Systems in Practice: Microcontrollers, Automation, and Connected Devices: Build Practical Applications with GPIO, Sensors, I2C, SPI, UART, IoT, Networking, Real-World Hardware
๐ Get Now: link.amazon/B0dBthguQ
aspashur retweeted
Quantum computing might sound like something people in long white coats do in secret labs somewhere.
But in this beginner-friendly guide, @casweb_dev teaches you how to build a quantum circuit in Python with Qiskit.
You'll learn about qubits, quantum gates, superposition, entanglement, Bell States, simulators, and more.
freecodecamp.org/news/how-toโฆ
aspashur retweeted
Ride or Die (2026)
At 50, assassin Judy is being pushed out. Her last shot: poison a target to look like a heart attack.
But the job didn't go as planned.
aspashur retweeted
For those of you working in R, an exciting package on urban morphology just landed on CRAN - geomorphR by @Jonathan Cohen! Hope to see this in Python soon!
It extracts geometric descriptors from building footprints stored as sf objects, so all you need is a bunch of polygons to describe urban form at any scale or feed it into ML models.
๐๐๐๐: cran.r-project.org/web/packaโฆ
๐๐ก๐ ๐๐๐ฐ ๐๐๐ข๐๐ง๐๐ ๐จ๐ ๐๐๐ฉ๐ฌ - thenewscienceofmaps.com/
aspashur retweeted
Whenever someone interacts with a website, that's potential data a marketer can analyze.
So how do they manage, wrangle, and make the best use out of that data?
In this book, Eva explains how to use Python to analyze data programmatically and discover helpful patterns.
freecodecamp.org/news/pythonโฆ
























