# Blog

Hi, I’m Lillie. Previously a magazine editor, I became a full-time mother and freelance writer in 2017. I spend most of my time with my kids and husband over at The Brown Bear Family but this blog is for my love of food and sharing my favorites with you!

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## Random Forest Algorithm

Random Forest is a robust machine-learning algorithm that is used for both classification and regression tasks. It is a type of ensemble learning method, which means that it combines multiple decision trees to create a more accurate and stable model. The mathematical intuition behind Random Forest is rooted in the concept of decision trees and…

## Decision Tree

Decision tree algorithms are a type of supervised learning algorithm used to solve both regression and classification problems. The goal is to create a model that predicts the value of a target variable based on several input variables. Decision trees use a tree-like model of decisions and their possible consequences, including chance event outcomes, resource…

## Support Vector Machine

Support Vector Machines (SVM) is a supervised machine learning algorithm that can be used for classification or regression tasks. The goal of the SVM algorithm is to find the hyperplane in an N-dimensional space that maximally separates the two classes. Mathematical Intuition Support Vector Machines (SVMs) are a type of supervised machine learning algorithm that…

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## C language

### Steps to Create a Tensorflow Model

There are 3 fundamental steps to creating a model Create a Model -> Connect the layers of NN yourself by using Sequential or Functional API or import a previously built model(Transfer Learning)Compile a Model -> Define how a model’s performance should be measured(metrics) and how to improve it by using an optimizer(Adam, SGD, etc.)Fit a…

### How to deal with outliers

In this Notebook, we will describe how to deal with outliers Trimming outliers from the dataset Performing winsorization Winsorizing is different from trimming because the extreme values are not removed, but are instead replaced byother values. Data greater than quantile 90 percent is replaced by value at 90 quantiles similarly less thenquantile 5 percent is…

### What is data leakage in Machine Learning

When training a machine learning model, we normally prefer selecting a generalized model which is performing well both on training and validation/test data. However, there can be a situation where the model performs well during testing but fails to achieve the same level of performance with real-world (production data) usage. For example, your model is…