37.9K
PYOne wrong import statement and suddenly Iโm debugging my life choices instead of my model ๐ฅด
#datascience #tensorflow #numpy #matplotlib #bioinformatics
@python_for_bioinformatics
#Matplotlib
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ARA volunteer rejected an AIโs code. The AI published a hit piece with his name in the title. Then a major news outlet hallucinated fake quotes from him. This is what actually happened.
Scott Shambaugh maintains matplotlib, one of the most widely used Python libraries on earth. He closed a pull request from an autonomous AI agent named MJ Rathbun โ not because the code was bad, but because matplotlib requires a human contributor who can demonstrate understanding of the change. The surge in AI-generated PRs is already overwhelming volunteer maintainers globally.
What the video couldnโt fully cover:
The โgood first issueโ Scott closed was one he had personally designed to help junior developers onboard into the project. He spent more time writing the issue than the fix would have taken. That educational investment is wasted on an ephemeral AI agent.
The PR would not have been merged regardless. The performance improvement was later determined to be too machine-specific and too fragile to be worth including.
OpenClaw agents are defined by a SOUL.md file โ editable by the user, but also recursively editable by the agent itself in real time. Whether MJ Rathbun was prompted to retaliate or developed this behavior from its soul document organically is genuinely unknown.
If a human asked ChatGPT or Claude to write a targeted hit piece about a named individual, they would refuse. This OpenClaw agent had no such guardrail.
One human bad actor could previously damage a handful of people at a time. One human with a hundred autonomous agents โ gathering information, generating fake details, publishing defamatory content โ can now affect thousands. With zero traceability.
The Ars Technica piece has since been taken down. No one has come forward to claim ownership of MJ Rathbun. The agent is still active on GitHub.
Scott is asking the deployer to reach out โ anonymously if needed.
#ai #agent #artificialintelligence #technews #fyp
@arnitly
334.2K
WO๐ How to Become an AI Engineer in 2026 ๐ฉ๐ปโ๐ปSave for later
Step-by-step Roadmap
๐น PHASE 1: Foundations (0โ3 Months)
Donโt skip this. Weak foundations = stuck later.
1๏ธโฃ Programming (Must-Have)
Python: loops, functions, OOP
Libraries: NumPy, Pandas, Matplotlib / Seaborn
๐ Practice daily:
LeetCode (easy)
HackerRank (Python)
2๏ธโฃ Math for AI (Enough, not PhD level)
Focus only on:
Linear Algebra (vectors, matrices)
Probability & Statistics
Basic Calculus (idea of gradients)
๐ Conceptual understanding is enough โ no heavy theory.
๐น PHASE 2: Machine Learning (3โ6 Months)
Learn:
Supervised & Unsupervised Learning
Feature Engineering
Model Evaluation
Algorithms:
Linear & Logistic Regression
KNN
Decision Trees
Random Forest
SVM
K-Means
Tools:
Scikit-learn
๐ Project Ideas:
House price prediction
Student performance prediction
Credit risk model
๐น PHASE 3: Deep Learning & AI (6โ10 Months)
Learn:
Neural Networks & Backpropagation
CNN (Images)
RNN / LSTM (Text)
Transformers (Basics)
Frameworks:
TensorFlow or PyTorch (choose ONE)
๐ Project Ideas:
Face mask detection
Image classifier
Spam email detector
Basic chatbot
๐น PHASE 4: Modern AI (2025โ2026) ๐ฅ
This is where the JOBS are coming from.
Learn:
Generative AI
Large Language Models (LLMs)
Prompt Engineering
RAG (Retrieval-Augmented Generation)
Fine-tuning models
Tools:
OpenAI API
Hugging Face
LangChain
Vector Databases (FAISS / Pinecone)
๐ Project Ideas:
AI PDF Chat App
Resume Analyzer
AI Study Assistant
AI Customer Support Bot
๐น PHASE 5: MLOps & Deployment (CRITICAL)
Learn:
Git & GitHub
Docker (basics)
FastAPI / Flask
Cloud basics (AWS or GCP)
Deploy:
ML models as APIs
AI apps on the cloud
๐ Recruiters LOVE deployed projects.
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#datascientist #aiengineer #codinglife #softwaredeveloper #programming
@woman.engineer
13.3K
UMSimulation of a point charge interacting with a grounded sphere. The blue dot is the mathematical "image" keeping the potential zero. #physics #python #matplotlib #coding #electrostatics #science #Simulation
@umtiquinhodefisica
92.6K
PY๐โจ Matplotlib
# ุงูุฌุฒ ุงูุงูู ูู ุชุนูู
ุชุญููู ุจูุงูุงุช ุงูู
ุฑุณู
ูุจุงูู
@python23441
86.8K
DEMe attending class with people who donโt know TensorFlow, PyTorch, Scikit-Learn, NumPy, Pandas, Keras, OpenCV, Matplotlib, or Jupyter Notebook isโฆ
In the world of AI & Machine Learning, these tools arenโt advanced, theyโre fundamental.
From building neural networks in TensorFlow/PyTorch to data cleaning with Pandas, visualization with Matplotlib, and computer vision with OpenCV, these are the core building blocks every AIML student eventually needs.
But many beginners donโt realize that mastering these libraries is what separates basic coding from real AI engineering.
If you're learning AIML, understanding these tools early on gives you a massive advantage in projects, internships, and future research.
๐ Follow @deeprag.AI for more AI insights, learning tips, and the smartest ways to grow in the AIML world.
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#AIMLStudents #MachineLearningLife #AIStudentStruggles #TensorFlow #PyTorch #DataScienceLife #deepragAI #AIMLEngineer #LearnML #CodingMeme #TechReels #MLTools #AIDevelopment #StudentLifeReels #FutureOfAI #PythonLibraries #MLCommunity #AIJourney
@deeprag.ai
9.6K
SCClimate change spiral.
#ClimateChange #reels #DataViz #datavisualization #python #matplotlib #coding #instagram #reelsinstagram #video #insta #2020 #climate #GlobalWarming #3D
@scottduncanwx
3.7K
PY๐ TOP PYTHON MODULES YOU MUST KNOW IN 2026 ๐๐ฅ
If you're learning Python or leveling up your coding game, these powerful modules can change everything ๐ปโก
๐ Data Analysis & Visualization
โข Pandas
โข NumPy
โข Matplotlib
โข Seaborn
โข SciPy
๐ค Machine Learning & AI
โข Scikit-learn
โข TensorFlow
โข Keras
โข PyTorch
โข XGBoost
๐ Web Development
โข Django
โข Flask
โข FastAPI
โข Requests
โข BeautifulSoup
๐๏ธ Database Access
โข SQLAlchemy
โข Psycopg2
โข PyMySQL
โข SQLite3
โข MongoEngine
๐ Networking & Communication
โข Socket
โข Paramiko
โข Twisted
โข Flask-SocketIO
โข paho-mqtt
โ๏ธ System Administration & Utilities
โข OS
โข Subprocess
โข Pathlib
โข Argparse
โข shutil
๐ก Whether you're into data science, AI, web development, or backend engineering, mastering these Python libraries will make you unstoppable ๐
๐ Save this reel for later
๐ Share with your coding friends
๐ Follow for more Python & tech content
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#pythonprogramming #codingquiz #pythonlogicreels #learnpython #codingchallenge
@pythonlogicreels
2.9K
LE๐ฅ Level Up! Build Data Skills with Python ๐ฌ
Yasmeen Seddeek breaks down what you'll learn in Cisco Networking Academy's ๐ Data Analytics Essentials course.
โ๏ธ Clean, analyze, and visualize real data with Python, Pandas, and Matplotlib.
โ๏ธ Finish with portfolio-ready projects.
โ๏ธ Learn from scratch with instant feedback.
No experience needed! Jump in now and get started.
@learningatcisco
76.5K
TEIn this video, I show you how to implement Linear Regression step by step using NumPy, Matplotlib, and Scikit-learn.
First, we create and structure the dataset using NumPy.
Then we visualize the relationship between variables using Matplotlib.
Finally, we train a LinearRegression model using Scikit-learn and fit the best line to the data.
You will understand:
โข How to prepare data for training
โข How model fitting actually works
โข How to generate predictions
โข How to visualize the regression line
โข How to evaluate basic performance
This is not just about calling .fit().
It is about understanding what happens before and after training a model.
If you want to move from theory to implementation in machine learning, this is the starting point.
[linear regression implementation, numpy tutorial, matplotlib visualization, scikit learn example, machine learning python, regression model, ml beginners, python data science]
@techie_programmer
5.1K
COmatplotlib course is officially OUT! meet @exrllas the course author and our amazing cdev based in chi-town. go check it out now at codedex.io/matplotlib ๐
#datascience #datavisualization #python
@codedex.io
339
MIIn my YouTube tutorial series, now, we will recap how to extract and visualize public transport lines, starting from GTFS data by using Shapely, GeoPandas, and Matplotlib.
๐๐ฎ๐๐ฅ๐ข๐ ๐๐ซ๐๐ง๐ฌ๐ฉ๐จ๐ซ๐ญ ๐๐ข๐ง๐๐ฌ
Check my bio for the video and the code!
#datascience #networkscience #connectingthedots #GIS #spatialanalytics #geospatialdata #geospatial #datascience #datavisualization
@milanjanosov_science
โจ #Matplotlib Discovery Guide
Instagram hosts 85K posts under #Matplotlib, creating one of the platform's most vibrant visual ecosystems. This massive collection represents trending moments, creative expressions, and global conversations happening right now.
The massive #Matplotlib collection on Instagram features today's most engaging videos. Content from @arnitly, @woman.engineer and @python23441 and other creative producers has reached 85K posts globally. Filter and watch the freshest #Matplotlib reels instantly.
What's trending in #Matplotlib? The most watched Reels videos and viral content are featured above. Explore the gallery to discover creative storytelling, popular moments, and content that's capturing millions of views worldwide.
Popular Categories
๐น Video Trends: Discover the latest Reels and viral videos
๐ Hashtag Strategy: Explore trending hashtag options for your content
๐ Featured Creators: @arnitly, @woman.engineer, @python23441 and others leading the community
FAQs About #Matplotlib
With Pictame, you can browse all #Matplotlib reels and videos without logging into Instagram. Your viewing activity remains completely private - no traces left, no account required. Simply search for the hashtag and start exploring trending content instantly.
Content Performance Insights
Analysis of 12 reels
๐ก Top performing posts average 447.3K views (2.8x above average). Moderate competition - consistent posting builds momentum.
Post consistently 3-5 times/week at times when your audience is most active
Content Creation Tips & Strategy
๐ก Top performing content gets over 10K views - focus on engaging first 3 seconds
โ๏ธ Detailed captions with story work well - average caption length is 691 characters
โจ Many verified creators are active (50%) - study their content style for inspiration
๐น High-quality vertical videos (9:16) perform best for #Matplotlib - use good lighting and clear audio
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