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Graduate in Physics, Master in Applied Geophysics from IIT Bombay, India. Machine Learning is my favourite topic of study and is widely used at present.
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Create a model and then use migration. The model defines the database. In "app" folder, open model.py file and modify it accordi...
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# Stochastic Gradient Descent method # dev is for evaluation from sklearn.datasets import make_classification from sklearn.metrics impor...
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As mentioned in the Introduction, Supervised learning is one of the algorithms of Machine Learning. Before going to discuss further, let... -
Shrinkage Method: Subset selection produces a model that is interpretable and has possibly lower prediction error than the full model. H... -
#creating superuser python3 manage.py createsuperuser # it will ask some values as below, (password is case-sensitiv...
About Me
Popular Posts
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Create a model and then use migration. The model defines the database. In "app" folder, open model.py file and modify it accordi...
-
# Stochastic Gradient Descent method # dev is for evaluation from sklearn.datasets import make_classification from sklearn.metrics impor...
-
As mentioned in the Introduction, Supervised learning is one of the algorithms of Machine Learning. Before going to discuss further, let... -
Shrinkage Method: Subset selection produces a model that is interpretable and has possibly lower prediction error than the full model. H... -
#creating superuser python3 manage.py createsuperuser # it will ask some values as below, (password is case-sensitiv...
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Hierarchical clustering is a method of cluster analysis which sets to build a hierarchy of clusters. Strategies for hierarchical clusteri...
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The EM algorithm is used to find the (locally) maximum likelihood parameters of a statistical model in cases where the equations cannot...
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Advantage and Disadvantage of Hierarchical algorithm: Advantages Disadvantage Does not require a number o...
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The linear model with more than one feature inputs are called multiple linear regression model. Suppose we have a univariate model with ... -
Stochastic Gradient Descent: Instead of considering all the samples together, we take samples one by one. Find whether the sample is corr...