Discover and read the best of Twitter Threads about #featureEngineering

Most recents (4)

12 Best FREE #SQL Courses and Certifications Online in 2023 — compiled by @tut_ml
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#Databases #DataScience #BigData #Analytics #DataScientists #100DaysOfCode
mltut.com/best-free-sql-…
#SQL Notes for Professionals: books.goalkicker.com/SQLBook/
[free 166-page PDF download]
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#Database #DataScience #DataAnalytics #DataScientists #DataProfiling
Read 4 tweets
#SupervisedLearning is a type of #MachineLearning where an algorithm is trained on a labeled dataset to predict outcomes for new data

The labeled dataset contains input variables and the desired output, and the algorithm uses this information to make predictions
In #SupervisedLearning, the algorithm is constantly adjusting its parameters to minimize the prediction error

One of the most popular algorithms for #SupervisedLearning is #LinearRegression, used for prediction problems where the target is continuous
Another common algorithm is #LogisticRegression, used for classification problems where the target is binary

#DecisionTrees and #RandomForests are commonly used for both regression and classification problems
Read 15 tweets
(Thread) Here is a short summary of "Rules of ML" by Martin Zinkevich (developers.google.com/machine-learni…). The #MachineLearning life cycle should consist of three phases:
Phase 0
- Launch the product without #MachineLearning . Collect #Data
Phase 1
- Building the first basic/transparent #model
- Make the #infrastructure right
- Monitor the right set of #metrics
- System should get a boost with a simple model itself
Phase 2
- More #FeatureEngineering on top of simple model (Low hanging fruits). #Regularization.
- Multiple launches with new features
- Metrics should still be rising with each launch
Read 4 tweets

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