#featureengineering ผลการค้นหา

Data you ignore: ambient humidity, operator shifts, batch age. Often the secret features. #FeatureEngineering

Day 14: The Undisputed King of Model Performance Took a short break, but now we're diving into one of the most critical chapters: Feature Engineering. This is where models are truly made or broken. 🧵 #MachineLearning #FeatureEngineering #MLOps

Feature engineering shapes model success! Handle missing data, scale continuous features, encode categories, & select top predictors to boost accuracy and reduce noise. Read more: nomidl.com/machine-learni… #ML #FeatureEngineering #DataScience #Preprocessing

✅ Just learned about Binarization in ML! Turned numeric features into binary (0/1) based on a threshold ⚡ Simple, but super useful for certain models & sparse data! One more tool added to my feature engineering toolkit 🔧 #MachineLearning #FeatureEngineering #100DaysOfML

🔢 Label Encoding Converts categories into numbers: Maharashtra → 3 Tamil Nadu → 4 Delhi → 0 Karnataka → 2 Gujarat → 1 Uttar Pradesh → 5 ⚠️ Simple, but risky! Models may wrongly assume an order between states. #DataScience #ML #FeatureEngineering

📊 Ordinal Encoding When categories have a natural order, we map them to numbers: Poor → 1 Good → 2 Very Good → 3 Excellent → 4 👉 ML models can now understand the ranking! #MachineLearning #DataScience #FeatureEngineering

📊 One-Hot Encoding in action! Instead of assigning numbers that may imply order (Red=1, Yellow=2, Green=3 ), we create binary columns: Red → [1,0,0] Yellow → [0,1,0] Green → [0,0,1] 👉 Keeps categories unbiased! #DataScience #ML #FeatureEngineering

Boost your ML model performance with feature engineering! 🚀 Transform, create, and select features to make your data smarter. 💡 Start small, experiment, and watch your models shine! #MachineLearning #AI #FeatureEngineering #DataScience #MLTips

💡 Quick Feature Engineering hacks: Dates → day/week/month Text → word counts & sentiment Missing values → don’t panic, just impute! Better features, better predictions. 🚀 #MLTips #FeatureEngineering #AI

Great models start with great features: normalize, encode, combine, transform. A small tweak can boost performance! #MachineLearning #FeatureEngineering #MLTips

🔑 Feature Engineering transforms raw data into valuable insights! From encoding categories to scaling numbers, it enhances model performance. Better features = better predictions. 🚀 #MachineLearning #DataScience #FeatureEngineering

📊 Just learned about Feature Scaling & Encoding in ML! ⚡ Feature Scaling – bring features to similar range ⚡ Encoding – convert categorical → numbers 👉 Both are must for model performance! #MachineLearning #DataScience #FeatureEngineering

Smarter AI starts with better context. mindzie helps enrich AI feature engineering by providing structured process data, making your models more accurate and reliable. 👉 Get started: mindzie.com/desktop-editio… #AI #featureengineering #processmining #dataanalytics

Speed up XGBoost training by 46x with one parameter change. Learn how GPU acceleration saves hours, boosts iteration, and scales to big data. - hackernoon.com/stop-waiting-m… #featureengineering #xgboost

Remember these ways to do #FeatureEngineering, perform #SQL-style queries, and how to work with our #Flatline editor. These #DataTransformations will be very useful to prepare your data for your #MLprojects! bigml.com/releases/summe… #MachineLearning #BigML #MLplatform

#FeatureEngineering allows us to transform raw data into detection by extracting features like elevation, slope & mineral composition from the ground. By combining them with chemical analysis, we can predict #emerald presence more efficiently!💎 Read.

Our very own @maryk_analyst took us through the techniques and strategies for data transformation under our topic of the week #FeatureEngineering. She's completing her degree in #BBIT, and yes, she's a good teacher/coach/guide/instructor.

🚀Feature Engineering for Deep Learning | 360DigiTMG 📅 Date: 25th August 2025 🕓 Time: 4:00 PM IST 📝 Register Now by clicking the link below 👇 360digitmg.zoom.us/webinar/regist… #FeatureEngineering #DeepLearning #AI #MachineLearning #DataScience #360DigiTMG #AITraining

#FeatureEngineering in Practice — Approaching (Almost) Any #MachineLearning Problem! ⬇️ Get book: amzn.to/2XJUczh by @abhi1thakur (4X @Kaggle Grandmaster) -or- Download PDF copy: github.com/abhishekkrthak… ————— #BigData #AI #DataScience #DataScientists #DeepLearning #Python

All you need to know about Feature Engineering 👇 #machinelearning #FeatureEngineering serokell.io/blog/feature-e…

Why Are Feature Engineering Techniques Essential for Data Analysis? itdigest.com/computer-scien… #dataanalysis #engineering #FeatureEngineering #ITDigest #PrincipalComponentAnalysis #TechniquesEssentialun #conventionaltechniques

"Soledad Galli provides a comprehensive guide to feature engineering in Python" --Russell Pollari, CEO of SharpestMinds Pick up the book here: packt.link/j3T5H #MachineLearning #FeatureEngineering #Python #Tensforflow #Pytorch

A Tutorial on Time Series #FeatureEngineering! #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java v#GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode geni.us/Series-Feature…

Feature Engineering: The Secret to Better Models! Feature Engineering is where data scientists turn raw data into gold! ✨ I'm learning how to clean & transform data for better model accuracy. Have you tried Feature Engineering before? 🤔 #FeatureEngineering #DataScience

[対談動画公開] dotData社CEOの藤巻遼平氏と弊社CSO 鈴木いっぺいとの対談動画です。 #生成ai #featureengineering hubs.ly/Q02gSNLX0

7 of the Most Used-#FeatureEngineering Techniques. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode geni.us/Hands-on-Featu…

Both Pandas and Polars are robust data manipulation tools, but their syntaxes differ subtly. Polars tends to use more explicit, verb-based methods, while Pandas leverages more concise bracket notation. #DataScience #pandas #FeatureEngineering #DataPreprocessing

Integrating atmospheric chemical reactions and #FeatureEngineering into a #MachineLearning model to investigate the various HONO contributing sources & to assess the kinetic parameters governing the primary HONO formation pathways. #Aerosols ES&T: go.acs.org/bX9

#Python #FeatureEngineering Cookbook with 70+ recipes for creating, engineering, & transforming features for #MachineLearning models (2nd Ed.): amzn.to/3Ssdh5X by @Soledad_Galli — #AI #DataStrategy #DataLiteracy #DataScience #DataScientist ➕ See her course:…

A Tutorial on Time #FeatureEngineering! #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java v#GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode geni.us/Series-Feature…

Happy Friday! #ICYMI we have added @bytewax to show the streaming side of our "write once & run anywhere" #featureengineering example. With Hamilton you can have a whole feature + #ML pipeline set up & easily change what you need to execute for #batch, #streaming, & #online. 1/3

🚀 Built an AI agent using CrewAI and llama-3.3-nemotron-super-49b-v1 for feature engineering! It suggests new features & writes Python code—saving hours for data scientists. Want to see it in action? Drop a 🔥! 💡 #AI #DataScience #featureengineering