@tandfresearch.bsky.social @amstatnews.bsky.social #LinearRegression #Simulation www.tandfonline.com/doi/full/10....
@tandfresearch.bsky.social @amstatnews.bsky.social #LinearRegression #Simulation www.tandfonline.com/doi/full/10....
www.originlab.com/fileExchange... #OriginPro #GLR #GeneralLinearRegression #LinearRegression #EffectPlot #DOE #DesignofExperiments
www.originlab.com/fileExchange... #OriginPro #GLR #GeneralLinearRegression #LinearRegression #EffectPlot #DOE #DesignofExperiments
https://thierrymoudiki.github.io/blog/2025/06/14/python/xgboost-default-overfitting
#Techtonique #DataScience #Python #rstats #MachineLearning
https://thierrymoudiki.github.io/blog/2025/06/14/python/xgboost-default-overfitting
#Techtonique #DataScience #Python #rstats #MachineLearning
#SumProg25 #ICPSR #LinearRegression #NonlinearModels
#SumProg25 #ICPSR #LinearRegression #NonlinearModels
#freeonlinelearning #colisty #courselist #sas/stat #statisticalanalysis #linearregression #logisticregression
colisty.netlify.app/courses/sas-...
#freeonlinelearning #colisty #courselist #sas/stat #statisticalanalysis #linearregression #logisticregression
colisty.netlify.app/courses/sas-...
www.originlab.com/fileExchange...
#GLR #GeneralLinearRegression #LinearRegression #StepwiseRegression #DOE #DesignofExperiments #OriginPro #OriginPro2025b #originlab
www.originlab.com/fileExchange...
#GLR #GeneralLinearRegression #LinearRegression #StepwiseRegression #DOE #DesignofExperiments #OriginPro #OriginPro2025b #originlab
#SixSigma #LeanManufacturing #GreenBelt #BlackBelt
#QualityImprovement #QualityControl #DOE#SPC #LinearRegression #GLR #MLR #GageStudy #ToleranceInterval #OriginPro
#SixSigma #LeanManufacturing #GreenBelt #BlackBelt
#QualityImprovement #QualityControl #DOE#SPC #LinearRegression #GLR #MLR #GageStudy #ToleranceInterval #OriginPro
https://thierrymoudiki.github.io/blog/2025/06/14/python/xgboost-default-overfitting
#Techtonique #DataScience #Python #rstats #MachineLearning
https://thierrymoudiki.github.io/blog/2025/06/14/python/xgboost-default-overfitting
#Techtonique #DataScience #Python #rstats #MachineLearning
1. Campaign performance
2. Sales & revenue
3. Housing price predictions
4. Financial forecasting
5. Medical diagnoses
Trick question! It's all of them.
More:
🔗 calibrate-analytics.com/insights/202...
1. Campaign performance
2. Sales & revenue
3. Housing price predictions
4. Financial forecasting
5. Medical diagnoses
Trick question! It's all of them.
More:
🔗 calibrate-analytics.com/insights/202...
thierrymoudiki.github.io/blog/2025/06...
#python #machinelearning
thierrymoudiki.github.io/blog/2025/06...
#python #machinelearning
amitdhanani.in/2025/02/15/h...
#machinelearning #python #linearregression #ml #mlwithoutlibrary #pythonml #supervisedLearning
amitdhanani.in/2025/02/15/h...
#machinelearning #python #linearregression #ml #mlwithoutlibrary #pythonml #supervisedLearning
Funded by @CLAND_saclay with @MiaParisSaclay @AgroParisTech @CIRAD
▶️More detail lnkd.in/e5PRxSQM via @IOPenvironment
Funded by @CLAND_saclay with @MiaParisSaclay @AgroParisTech @CIRAD
▶️More detail lnkd.in/e5PRxSQM via @IOPenvironment
These models help predict numbers, trends & patterns.
Example: Want to train your own regression model and predict how coffee affects your sleep? regression-js has got you covered!
#linearregression #regression #mlmodels
https://buff.ly/3VfPwPF
These models help predict numbers, trends & patterns.
Example: Want to train your own regression model and predict how coffee affects your sleep? regression-js has got you covered!
#linearregression #regression #mlmodels
https://buff.ly/3VfPwPF
Short video for details: youtu.be/BxfNyDzULmg
#rstats #statistics #dataanalysis #stats #datascience #r4ds #linearregression
Short video for details: youtu.be/BxfNyDzULmg
#rstats #statistics #dataanalysis #stats #datascience #r4ds #linearregression
The focus now shifts from training to understanding performance over time.
Monitoring is where real MLOps begins 🚀
#MLOpsZoomcamp #DataTalksClub
The focus now shifts from training to understanding performance over time.
Monitoring is where real MLOps begins 🚀
#MLOpsZoomcamp #DataTalksClub
import pandas as pd
from sklearn.linear_model import LinearRegression
df = pd.read_csv('mtcars.csv')
X = df[['wt']]
y = df['mpg']
model = LinearRegression().fit(X, y)
print(f"Slope: {model.coef_[0]}, Intercept: {model.intercept_}")
I was teaching python users R today and I was shocked that they were impressed the most with lm() and that you can do linear regression in 1-2 lines of code
We couldn't get beyond that in the training. Such an interesting experience.
import pandas as pd
from sklearn.linear_model import LinearRegression
df = pd.read_csv('mtcars.csv')
X = df[['wt']]
y = df['mpg']
model = LinearRegression().fit(X, y)
print(f"Slope: {model.coef_[0]}, Intercept: {model.intercept_}")