Robert Collinsselfenrichment.hashnode.dev·Jul 6, 2023color optimization problems in pythonYou wouldn't think that artists might have a legitimate use for an optimization library like cvxpy or sk learn. 😃 This document acts as an addendum and starting point to look into this small python library I created at the beginning of the year: Col...DiscussPython
Aswin Lalaswnss.hashnode.dev·Jun 29, 2023Sentiment Analysis with Naive Bayes Classifier using NLTK and Scikit-learnIntroduction: In this blog post, we will explore how to perform sentiment analysis on movie reviews using the Naive Bayes classifier. Sentiment analysis is a popular task in natural language processing that involves determining the sentiment or opini...Discussnlp
Abhay swarnakarabhayswarnakar.hashnode.dev·Jun 28, 2023Feature ScalingFeature scaling is a data preprocessing technique that involves transforming the value of features or variables in a dataset to a similar scale. Feature scaling can vary your results a lot while using certain algorithms and have minimal or no effect ...Discuss·1 like·36 readsPython 3
MemgraphforMemgraphmemgraph.hashnode.dev·Jun 12, 2023Understanding Cosine Similarity in Python with Scikit-LearnCosine similarity proved useful in many different areas, such as in machine learning applications, natural language processing, and information retrieval. After reading this article, you will know precisely what cosine similarity is, how to run it wi...Discusssklearn
Rhythm Rawatrhythmblogs.hashnode.dev·Apr 8, 2023Supervised Machine Learning Series:Decision trees(3rd Algorithm)Decision trees are one of the most popular and widely used machine learning algorithms. They are easy to understand and interpret, making them ideal for both beginners and experts alike. A decision tree is a tree-like structure that represents decisi...Discuss·1 like·56 readsMachine Learning
Bhagirath Deshani bhagirathkd.hashnode.dev·Jan 6, 2023#33 Machine Learning & Data Science Challenge 33What is the pipeline in sklearn? A pipeline is what chains several steps together, once the initial exploration is done. For example, some codes are meant to transform features—normalize numerically, turn text into vectors, or fill up missing data,...Discuss·33 readsMachine Learning & Data Science Interview ChallengesMachine Learning
Rick Hallblog.rickslearning.com·Nov 17, 2022Incorporate custom functions in sklearn pipelineI was working on a tabular dataset problem on Kaggle, and I wrote a function to do some preprocessing. The function removed columns that had a correlation above a threshold. I wanted to experiment with different thresholds, and rather than tune it by...Discuss·31 readssklearn
yoonminrollingdev.hashnode.dev·Aug 16, 2022Feature ControlGet in mind that I'm using... # checkout variable names. from sklearn.model_selection import train_test_split x_train, x_test, y_train, y_test = train_test_split(<data>, <target>) Transformer sklearn.preprocessing.PolynomialFeatures adds additiona...DiscussDatasklearn
Uddeepta Raaj Kashyapuddeepta.hashnode.dev·Jun 23, 2022Implementing a Simple Linear Regression Machine Learning ModelIntroduction Suppose we are given a dataset where based on the area of the house, the prices are listed. We are asked to prepare a Machine Learning model which predicts the prices of the house based on the area of house that we supply as input to the...Discuss·32 likes·273 readsMachine Learning
