37.9K
PYOne wrong import statement and suddenly I’m debugging my life choices instead of my model 🥴
#datascience #tensorflow #numpy #matplotlib #bioinformatics
@python_for_bioinformatics
#Matplotlib
Dünyanın dört bir yanından insanlardan Matplotlib hakkında 85K Reels videosu izle.
Giriş yapmadan anonim olarak izle.
85K posts
NewTrendingViral
İlgili Aramalar
30Trend Reels
(12)
1.3M
ARA volunteer rejected an AI’s 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 — 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 couldn’t fully cover:
The “good first issue” 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 — 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 — gathering information, generating fake details, publishing defamatory content — 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 — anonymously if needed.
#ai #agent #artificialintelligence #technews #fyp
@arnitly
336.4K
WO🚀 How to Become an AI Engineer in 2026 👩🏻💻Save for later
Step-by-step Roadmap
🔹 PHASE 1: Foundations (0–3 Months)
Don’t skip this. Weak foundations = stuck later.
1️⃣ Programming (Must-Have)
Python: loops, functions, OOP
Libraries: NumPy, Pandas, Matplotlib / Seaborn
📌 Practice daily:
LeetCode (easy)
HackerRank (Python)
2️⃣ Math for AI (Enough, not PhD level)
Focus only on:
Linear Algebra (vectors, matrices)
Probability & Statistics
Basic Calculus (idea of gradients)
📌 Conceptual understanding is enough — no heavy theory.
🔹 PHASE 2: Machine Learning (3–6 Months)
Learn:
Supervised & Unsupervised Learning
Feature Engineering
Model Evaluation
Algorithms:
Linear & Logistic Regression
KNN
Decision Trees
Random Forest
SVM
K-Means
Tools:
Scikit-learn
📌 Project Ideas:
House price prediction
Student performance prediction
Credit risk model
🔹 PHASE 3: Deep Learning & AI (6–10 Months)
Learn:
Neural Networks & Backpropagation
CNN (Images)
RNN / LSTM (Text)
Transformers (Basics)
Frameworks:
TensorFlow or PyTorch (choose ONE)
📌 Project Ideas:
Face mask detection
Image classifier
Spam email detector
Basic chatbot
🔹 PHASE 4: Modern AI (2025–2026) 🔥
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)
📌 Project Ideas:
AI PDF Chat App
Resume Analyzer
AI Study Assistant
AI Customer Support Bot
🔹 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
📌 Recruiters LOVE deployed projects.
.
.
.
#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
93.2K
PY📊✨ Matplotlib
# الجز الاول في تعلم تحويل بيانات الى
رسم يباني
@python23441
86.8K
DEMe attending class with people who don’t know TensorFlow, PyTorch, Scikit-Learn, NumPy, Pandas, Keras, OpenCV, Matplotlib, or Jupyter Notebook is…
In the world of AI & Machine Learning, these tools aren’t advanced, they’re 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 don’t 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.
👉 Follow @deeprag.AI for more AI insights, learning tips, and the smartest ways to grow in the AIML world.
.
.
.
.
#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
3.8K
PY🚀 TOP PYTHON MODULES YOU MUST KNOW IN 2026 🐍🔥
If you're learning Python or leveling up your coding game, these powerful modules can change everything 💻⚡
📊 Data Analysis & Visualization
• Pandas
• NumPy
• Matplotlib
• Seaborn
• SciPy
🤖 Machine Learning & AI
• Scikit-learn
• TensorFlow
• Keras
• PyTorch
• XGBoost
🌐 Web Development
• Django
• Flask
• FastAPI
• Requests
• BeautifulSoup
🗄️ Database Access
• SQLAlchemy
• Psycopg2
• PyMySQL
• SQLite3
• MongoEngine
🌐 Networking & Communication
• Socket
• Paramiko
• Twisted
• Flask-SocketIO
• paho-mqtt
⚙️ System Administration & Utilities
• OS
• Subprocess
• Pathlib
• Argparse
• shutil
💡 Whether you're into data science, AI, web development, or backend engineering, mastering these Python libraries will make you unstoppable 🚀
👉 Save this reel for later
👉 Share with your coding friends
👉 Follow for more Python & tech content
.
.
.
.
.
#pythonprogramming #codingquiz #pythonlogicreels #learnpython #codingchallenge
@pythonlogicreels
2.9K
LE🎥 Level Up! Build Data Skills with Python 🎬
Yasmeen Seddeek breaks down what you'll learn in Cisco Networking Academy's 🆓 Data Analytics Essentials course.
❇️ Clean, analyze, and visualize real data with Python, Pandas, and Matplotlib.
❇️ Finish with portfolio-ready projects.
❇️ Learn from scratch with instant feedback.
No experience needed! Jump in now and get started.
@learningatcisco
76.8K
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:
• How to prepare data for training
• How model fitting actually works
• How to generate predictions
• How to visualize the regression line
• 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 📈
#datascience #datavisualization #python
@codedex.io
341
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.
𝐏𝐮𝐛𝐥𝐢𝐜 𝐓𝐫𝐚𝐧𝐬𝐩𝐨𝐫𝐭 𝐋𝐢𝐧𝐞𝐬
Check my bio for the video and the code!
#datascience #networkscience #connectingthedots #GIS #spatialanalytics #geospatialdata #geospatial #datascience #datavisualization
@milanjanosov_science
✨ #Matplotlib Keşif Rehberi
Instagram'da #Matplotlib etiketi altında 85K paylaşım bulunuyor ve platformun en canlı görsel ekosistemlerinden birini oluşturuyor. Bu devasa koleksiyon, şu an gerçekleşen trend anları, yaratıcı ifadeleri ve küresel sohbetleri temsil ediyor.
#Matplotlib etiketi, Instagram dünyasında şu an en çok ilgi gören akımlardan biri. Toplamda 85K üzerinde paylaşımın bulunduğu bu kategoride, özellikle @arnitly, @woman.engineer and @python23441 gibi üreticilerin videoları ön plana çıkıyor. Pictame ile bu popüler içerikleri anonim olarak izleyebilirsiniz.
#Matplotlib dünyasında neler viral? En çok izlenen Reels videoları ve viral içerikler yukarıda yer alıyor. Yaratıcı hikaye anlatımını, popüler anları ve dünya çapında milyonlarca görüntüleme alan içerikleri keşfetmek için galeriyi inceleyin.
Popüler Kategoriler
📹 Video Trendleri: En yeni Reels içeriklerini ve viral videoları keşfedin
📈 Hashtag Stratejisi: İçerikleriniz için trend hashtag seçeneklerini inceleyin
🌟 Öne Çıkanlar: @arnitly, @woman.engineer, @python23441 ve diğerleri topluluğa yön veriyor
#Matplotlib Hakkında SSS
Pictame ile Instagram'a giriş yapmadan tüm #Matplotlib reels ve videolarını izleyebilirsiniz. Hesap gerekmez ve aktiviteniz gizli kalır.
İçerik Performans Analizi
12 reel analizi
💡 En iyi performans gösteren içerikler ortalama 449.2K görüntüleme alıyor (ortalamadan 2.8x fazla). Orta seviye rekabet - düzenli paylaşım momentum oluşturur.
Kitlenizin en aktif olduğu saatlerde haftada 3-5 kez düzenli paylaşım yapın
İçerik Oluşturma İpuçları & Strateji
💡 En iyi içerikler 10K üzeri görüntüleme alıyor - ilk 3 saniyeye odaklanın
📹 #Matplotlib için yüksek kaliteli dikey videolar (9:16) en iyi performansı gösteriyor - iyi aydınlatma ve net ses kullanın
✍️ Hikayeli detaylı açıklamalar işe yarıyor - ortalama açıklama uzunluğu 691 karakter
✨ Çok sayıda onaylı hesap aktif (%50) - ilham almak için içerik tarzlarını inceleyin
#Matplotlib İle İlgili Popüler Aramalar
🎬Video Severler İçin
Matplotlib ReelsMatplotlib Reels İzle
📈Strateji Arayanlar İçin
Matplotlib Trend Hashtag'leriEn İyi Matplotlib Hashtag'leri
🌟Daha Fazla Keşfet
Matplotlib Keşfet#matplotlib updates 2026#matplotlib python#matplotlib library in python#matplotlib library for python#new matplotlib features#matplotlib static visualizations#matplotlib line chart example python#matplotlib latest features