What do you want to save?
Add Code snippet
New code examples
-
Python 2022-03-03 20:05:03
how to install face_recognition
# To install face_recognition. First download boost from http://www.boost.org/users/download/ # Then navigate to C:\Users\(Username)\AppData\Local\Programs\Python\(Python version)\Lib\site-packages # Move the boost file into that location and extract it #... Add solution -
Other 2022-02-27 11:10:04
bootstrap 4 link
<!-- Boostrap 4 CSS --> <link rel="stylesheet" href="https://stackpath.bootstrapcdn.com/bootstrap/4.4.1/css/bootstrap.min.css" integrity="sha384-Vkoo8x4CGsO3+Hhxv8T/Q5PaXtkKtu6ug5TOeNV6gBiFeWPGFN9MuhOf23Q9Ifjh" cross... Add solution -
Other 2022-02-23 04:20:03
mechanical keyboard
Is the mechanical keyboard right choice for programming? The answer is both yes and no. Yes, if you want a durable keyboard with a crisp feedback and want to get rid of that mushy feeling from those membrane keyboards then surely you can go for this. Wi... Add solution -
Python 2022-02-18 07:30:05
multiclass classification model
knn=KNeighborsClassifier() svc=SVC() lr=LogisticRegression() dt=DecisionTreeClassifier() gnb=GaussianNB() rfc=RandomForestClassifier() xgb=XGBClassifier() gbc=GradientBoostingClassifier() ada=AdaBoostClassifier() ------------------------------------------... Add solution -
Python 2022-02-01 23:21:02
Gradient-Boosted Trees (GBTs) learning algorithm for regression
# Gradient-Boosted Trees (GBTs) learning algorithm for regression from numpy import allclose from pyspark.ml.linalg import Vectors df = spark.createDataFrame([ (1.0, Vectors.dense(1.0)), (0.0, Vectors.sparse(1, [], []))], ["label", "fe... Add solution -
Other 2022-02-01 07:10:01
bootstrap code snippets
<!--link this to boostsrap--> <link href="https://maxcdn.bootstrapcdn.com/font-awesome/4.7.0/css/font-awesome.min.css" rel="stylesheet" /> <footer class="footer_area section_padding_130_0"> <div c... Add solution -
Python 2022-01-29 10:07:17
regression model
knn=KNeighborsRegressor() svr=SVR() lr=LinearRegression() dt=DecisionTreeRegressor() gbm=GradientBoostingRegressor() ada=AdaBoostRegressor() rfr=RandomForestRegressor() xgb=XGBRegressor() -------------------------------------------------------------------... Add solution