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This article will explain 3 types of regularizations and where and how to use them using Scikit-Learn.

Why use regularization?

First we need to understand why we should regularization. Regularization is mainly used so that a model does not overfit the data. It is mainly used in a polynomial model as it may have higher degree features which can cause the model to overfit, what regularization does is reduces the number of polynomial degrees which makes the model not overfit the data.

Now the advantage of using regularization over the other methods such as reducing the number of features in the training data…


Stratified Sampling

Creating a test set from your training dataset is one of the most important aspects of building a machine learning model.

This article shows why it is a good idea to consider using Stratified sampling while doing so.

Why stratified sampling?

  • It is used to eliminate sampling bias in a test set.
  • It allows to create a test set with a population that best represents the entire population being studied.
  • Stratified random sampling is different from simple random sampling, which involves the random selection of data from the entire population so that each possible sample is equally likely to occur.
  • If sampling bias…


In this tutorial I will explain how to sync your firestore database with your state, manged by Vuex in your Vue app using VuexFire.

So what is VueFire/VuexFire?

Vuexfire is a small and pragmatic solution to create realtime bindings between a Firebase RTDB or a Firebase Cloudstore and your Vuex store. Making it straightforward to always keep your store state in sync with remote databases.

Why use VuexFire

What VuexFire allows us to do is to keep our Firestore database in sync with the state of our app. For example, lets say you want to delete a document from you firestore collection it involves these steps:

  • Create…

Saaransh Menon

A Computer Science Engineering student exploring the amazing world of ML and DL. Also a web development enthusiast.

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