32.8K
MAMore like this? Do you like the in depth feature engineering vids?? Lmk 😅🫶🏻 :) #cleanaireacepace #featureengineering
@mar_antaya
#Feature Engineering
Schauen Sie sich Reels-Videos über Feature Engineering von Menschen aus aller Welt an.
Anonym ansehen ohne Anmeldung.
Ähnliche Suchen
30Trending Reels
(12)
518.1K
SAIdeas for your next engineering or creative project! ⭐️📀
Tutorials ⋆౨ৎ:
1. Music LED Box, by motadacruz on instructables.com
2. Infrared Home Intrusion System, by Florian Wilhelm Dirnberger on hackaday.io
3. Retro Style Radio, by mircemk on hackaday.io
4. LED Cube 8x8x8, by chr instructables.com
5. Multi-touch table, by Jamaal_7lna on instructables.com
#projectideas #engineeringproject #diyprojects #collegestudent #womeninstem
@sagecadence_
336.2K
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
1.2M
ME100k Views
Description**
Designing an impeller in SolidWorks is an essential skill for engineers working on pumps, turbines, and fluid-moving systems. By using tools like lofts, sweeps, circular patterns, and parametric modeling, you can efficiently create a high-performance impeller. This tutorial will guide you through the step-by-step process of designing an impeller with optimized blade profiles, ensuring smooth fluid flow and efficient energy conversion.
**Working and Uses**
The design process starts with sketching the hub and blade profiles, followed by applying loft or sweep features to create the impeller blades. Using circular patterns, the blades are replicated around the central axis for a symmetrical and balanced design.
Uses:
1. Designing pump impellers for efficient water and fluid movement.
2. Creating turbine impellers for improved energy conversion in power plants.
3. Developing blower and compressor impellers for industrial air circulation.
Follow @Mech_design_Nepal for more insights!
#Mech_design_Nepal #follow #share #reels #SolidWorks #ImpellerDesign #CADModeling #3DDesign #PumpEngineering #MechanicalEngineering #CFD #FluidDynamics #EngineeringDesign
@mech_design_nepal
76.7K
DEMachine Learning Math- Correlation Coefficient (r)
The correlation coefficient (r).... often called Pearson’s r measures the linear relationship between two variables. Values range from -1 (perfect negative correlation) through 0 (no linear relationship) to +1 (perfect positive correlation).
Why it matters for ML:
helps with feature selection (drop highly correlated features to avoid multicollinearity)
reveals whether input features move together or cancel each other out
guides preprocessing steps (scaling, PCA, regularization)
quick sanity-check before training complex models
Use this video to learn what r means visually, how to compute it, and real examples where checking correlation saves your model performance.
Credits: 3 minute data science
👉 Follow @deeprag.ai for more bite-sized ML math, practical tips, and growth hacks for AI creators.
.
.
.
#MachineLearning #DataScience #PearsonR #Correlation #FeatureEngineering #MLMath #Statistics #AI #DeepLearning #DataViz #deepragAI #LearnToCode #MLTips #EDA
@deeprag.ai
1.9K
SOContact us for help with simulations #cfd #ansys #engineering #engineeringsolutions #simulation
@solvenglabs
604
AIMore: @ai.artificialintelligence.ai
Steps for Feature Engineering! 5.Feature Iteration
@ai.artificialintelligence.ai
@ai.artificialintelligence.ai
@ai.artificialintelligence.ai
The team at oxfordrobots are developing solutions for robots to be able to perceive their environment and make intelligent decisions on how to move from one point to another.
➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
✔Turn post notifications on🔔
✔Follow, like, share and comment
➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
💨Disclaimer: No copyright infringement / DM for credits or post removal
💨source: Unknown / Above image belongs to respective owners or designers
💨 Image or content is used for nonprofit only
➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
.
.
.
.
.
.
.
No copyright intended, credit remains to respective owners.
#artificialintelligence #machinelearning #deeplearning #aiwithai #ai #datascience #dataanalytics #datascientist #datavisualization #featureengineering
#featureiteration
@ai.artificialintelligence.ai
81.0K
PE9 data projects ideas instead of doomscrolling:
(And there is a repo with the data :) )
🤖 Machine Learning Projects
* Diabetes Classification�Build and compare classification models to show how data preprocessing, feature scaling, and hyperparameter tuning directly improve predictive performance.
* Heart Attack Prediction�Implement an end-to-end classification pipeline—from raw data to model evaluation—to demonstrate a realistic machine learning workflow.
* Medical Cost Prediction�Train a regression model to predict healthcare costs, emphasizing feature importance analysis and model optimization to explain what drives predictions.
🛠️ Data Engineering Projects
* NBA Player Statistics ETL Pipeline�Design an ETL pipeline that extracts player statistics, cleans and transforms the data, and stores it in a relational database for reliable downstream analysis.
* Real-Time & Batch Data Pipelines with Kafka�Build a scalable pipeline that processes streaming and batch data using Kafka, PostgreSQL, and Docker to demonstrate modern data flow architecture.
* Glassdoor Job Data Pipeline�Scrape job postings, clean and structure the raw data, and prepare it for analysis and visualization to showcase real-world data ingestion challenges.
📊 Data Analytics Projects
* Pokémon Dataset Analysis�Perform exploratory data analysis and feature engineering to uncover patterns in Pokémon characteristics such as types, stats, and legendary status.
* Automated EDA Tool Comparison�Benchmark AutoViz, SweetViz, and Pandas Profiling across multiple datasets to evaluate performance, resource usage, and practical trade-offs.
* Exploratory Job Market Analysis�Analyze cleaned job posting data to extract trends, key skills, and role distributions using visualizations and summary statistics.
👉🏻 Comment « data » to get the link to the repo and portfolio strategies!
@penelope_data
206.5K
ADCAD (Onshape): Digital sculpting. Runs in your browser.
FEA (Simscale): Virtual stress testing.
Caution: Don’t spend 40 hours on a simulation when a 5-minute physical test will give you the answer.
CFD (Simscale): Digital wind tunnel. Great for guidance, but real-world air is the ultimate judge
#engineeringprojects #buildinpublic #futureengineers #engineeringstudents #aerospaceengineering
@adam.aero
22.3K
_JData Science ante model build cheyadam kaadu.
Data ni clean cheyadam, transform cheyadam, prepare cheyadam real skill.
Feature Engineering & Preprocessing —
70% of real-world ML work happens here.
Projects > Theory.
#DataScienceStudent #FeatureEngineering #MachineLearningJourney #PythonDeveloper #AIStudent BuildInPublic CodingLife DataProjects FutureDataScientist TechSkills
@_jyothikaaa
29.7K
MIWant to master FEA pre-processing? Here are the top courses that will teach you everything you need to know about using industry-leading tools like ANSA and HyperMesh! Whether you're prepping complex geometries or refining meshes for simulations, these courses will level up your skills and help you tackle any project with confidence. Get ready to transform your simulations!
.
.
.
.
.
.
.
.
.
.
.
#instagram #trendingreels #transition #reels #studygram #engineering #mechanicalengineering #FiniteElementAnalysis #viral #reelsinstagram #reelkarofeelkaro #reelitfeelit #career #careeradvice #reelsvideo #reelsviral #automobile #aerospace
@mindful.muscle_
120.7K
WAThe secret to circuit design #electronics #engineering
@wasstronics
✨ #Feature Engineering Entdeckungsleitfaden
Instagram hostet thousands of Beiträge unter #Feature Engineering und schafft damit eines der lebendigsten visuellen Ökosysteme der Plattform.
Entdecken Sie die neuesten #Feature Engineering Inhalte ohne Anmeldung. Die beeindruckendsten Reels unter diesem Tag, besonders von @mech_design_nepal, @sagecadence_ and @woman.engineer, erhalten massive Aufmerksamkeit.
Was ist in #Feature Engineering im Trend? Die meistgesehenen Reels-Videos und viralen Inhalte sind oben zu sehen.
Beliebte Kategorien
📹 Video-Trends: Entdecken Sie die neuesten Reels und viralen Videos
📈 Hashtag-Strategie: Erkunden Sie trendige Hashtag-Optionen für Ihren Inhalt
🌟 Beliebte Creators: @mech_design_nepal, @sagecadence_, @woman.engineer und andere führen die Community
Häufige Fragen zu #Feature Engineering
Mit Pictame können Sie alle #Feature Engineering Reels und Videos durchsuchen, ohne sich bei Instagram anzumelden. Kein Konto erforderlich und Ihre Aktivität bleibt privat.
Content Performance Insights
Analyse von 12 Reels
💡 Top-Posts erhalten durchschnittlich 573.6K Aufrufe (2.6x über Durchschnitt)
Regelmäßig 3-5x/Woche zu aktiven Zeiten posten
Content-Erstellung Tipps & Strategie
💡 Top-Content erhält über 10K Aufrufe - fokussieren Sie auf die ersten 3 Sekunden
📹 Hochwertige vertikale Videos (9:16) funktionieren am besten für #Feature Engineering - gute Beleuchtung und klaren Ton verwenden
✨ Viele verifizierte Creator sind aktiv (33%) - studieren Sie deren Content-Stil
✍️ Detaillierte Beschreibungen mit Story funktionieren gut - durchschnittliche Länge 742 Zeichen
Beliebte Suchen zu #Feature Engineering
🎬Für Video-Liebhaber
Feature Engineering ReelsFeature Engineering Videos ansehen
📈Für Strategie-Sucher
Feature Engineering Trend HashtagsBeste Feature Engineering Hashtags
🌟Mehr Entdecken
Feature Engineering Entdecken#engine#himalayan 450 engine features#unreal engine 5 game engine features#r15s engine features#apache rr310 engine features#engineer#feature#prius hybrid engine features