Explore tweets tagged as #FeatureEngineering
Day 9 of 365:.Got hands-on with feature engineering today 🔧.✔️ Learned how to clean & prep data for modeling.✔️ Explored one-hot encoding and other preprocessing techniques.Now I know how to make raw data ML-ready! 💻📊.#100DaysOfDataScience #DataScience #FeatureEngineering
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🍳 Feature Engineering = the secret sauce of ML! Transform raw data into smart features to unlock better predictions. Mix, create, and elevate your model’s flavor! 🔗 #FeatureEngineering #ML #AI #DataTransformation
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👉MICE is a powerful method for datasets with missing data across multiple variables. Let this slide guide you through how it works. #machinelearning #MICE #mlmodels #datascience #dataengineering #imputation #featureengineering
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🧹 Data Preprocessing = prepping your canvas before the ML masterpiece 🎨 From cleaning to scaling, it's the unsung hero behind great models. 🔗 #ML #DataPreprocessing #FeatureEngineering
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"Soledad Galli provides a comprehensive guide to feature engineering in Python" --Russell Pollari, CEO of SharpestMinds.Pick up the book here: #MachineLearning #FeatureEngineering #Python #Tensforflow #Pytorch
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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.
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🚖 Spent the day fine-tuning the NYC Taxi Trip Duration Prediction data pipeline!. ✅ Removed outliers.✅ Scaled & encoded features.✅ Automated train-test-val processing.Next up: Model training! 🚀.DataScience #MachineLearning #NYCTaxi #FeatureEngineering #100DaysOfCode
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Not all AI = GenAI. At the Port of Corpus Christi, AI is powering a digital twin to improve ship tracking & emergency response—no LLMs required. Great reminder that ML drives value in many ways. 👉 #AI #MachineLearning #PortTech #FeatureEngineering
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OMG I’ve got an Outlier!😟 What should I do❓. Outliers are data points that significantly diverge from the rest of the values in the variable. What should we do with them? . #DataScience #FeatureEngineering #MachineLearning. #dataanalyst #datascientist #outliers #data
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#Infographic: Unlocking the power of data requires a structured approach!. #ProblemDefinition #DataCollection #DataPreparation #DataExploration #FeatureEngineering #Modeling #ModelEvaluation #ModelDeployment #ModelMaintenance #DataScience
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#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.
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Improve your feature engineering process with MLFinLab! 🤖🔍 Our advanced tools and expert guidance help you navigate the ever-changing landscape of feature engineering . Learn more in our blog post👉.#machinelearning #DataScience #AI #featureengineering
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Great demo 👍 showing how correlation impacts feature importance in random forests. 🔗. #MachineLearning #DataScience #AI #RandomForest #FeatureEngineering #DataAnalytics
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10 models are better than 1. How can you combine the predictions of multiple models to improve the overall acuracy? . #machinelearning #mlmodels #datascience #dataengineer #ai #programming #featureengineering
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🏷️Deal of the Day🛒. How to improve your #machinelearning pipelines without hours spent on fine-tuning parameters? . The answer is #featureengineering: @Prof_OZ #ML #data
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When it comes to scaling data for machine learning models, I am frequently asked: . Can we not fit scalers on the full dataset? Why do we need to split into train and test sets? . Read the 🧵 for more details!👇. #FeatureEngineering #MachineLearning #DataScience
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🔍 Unlock the Power of Data: Create meaningful features that capture the essence of your problem. 🎯✨. #dataculture #datascience #careeradvice #dataanalytics #datagovernance #FeatureEngineering #Algorithm #DataAnalysis
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Here are some practical tips to tackle it head-on:. #FeatureEngineering #MachineLearning #DataScience
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