+ is 1. 5 and that is exactly the value of ζ in this case. Understanding CAs I mentioned above…
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Machine Learning with Python: NLP and text recognition
Machine Learning with Python: NLP and text recognitionRoberto SannazzaroBlockedUnblockFollowFollowingFeb 3In this article i would like to apply a series of…
Continue ReadingNLP Kaggle Competition
NLP Kaggle CompetitionIntroductory Notebook and Exploratory Data AnalysisTara BoyleBlockedUnblockFollowFollowingFeb 4The Quora Insincere Questions Classification competition is a natural language processing task…
Continue ReadingHow Did Twitter React To Gillette’s ‘Toxic Masculinity’ Ad: A Sentiment Analysis using R and Twitter’s API
How Did Twitter React To Gillette’s ‘Toxic Masculinity’ Ad: A Sentiment Analysis using R and Twitter’s APINathan RodriguesBlockedUnblockFollowFollowingJan 20Picture taken…
Continue ReadingHow Do People Feel About Saving Sea Turtles?
Sentiment Analysis of #savetheturtles tweets using…github. comHypothesisOverall, I thought I’d see a decline in interest over time. The below screenshot…
Continue ReadingConundrums of the Confusion Matrix
How do we know our model is better than any other model?This blog post will explain the metrics used to…
Continue ReadingMaking computers understand the sentiment of tweets
Making computers understand the sentiment of tweetsKristoffer Stensbo-SmidtBlockedUnblockFollowFollowingJan 11Understanding whether a tweet is meant as positive or negative is something humans…
Continue ReadingVarious ways to evaluate a machine learning model’s performance
Or a patient is having cancer (positive) or is found healthy (negative)..Some common terms to be clear with are:True positives…
Continue Reading資料結構大便當:Bloom Filter
資料結構大便當:Bloom FilterKadaiBlockedUnblockFollowFollowingDec 20Bloom Filter 介紹與實作大家好,我是 Kadai,本次要分享的是在後端 Redis 分享會第一次聽到的資料結構:Bloom Filter(布隆過濾器)簡介Bloom Filter(布隆過濾器)由 Burton Howard Bloom 在 1970 構思出來,用來測試一個元素是否存在特定集合中。hash table 也可以做到,那為什麼要使用 Bloom Filter…
Continue ReadingDealing With Class Imbalanced Datasets For Classification.
Undersampling.Say, you have 40,000 positive sample and 2,000 negative samples in your dataset..We will use this as our running example…
Continue ReadingSupervised Machine Learning: Classification
Similarly, a true negative is an outcome where the model correctly predicts the negative class.False Positive & False NegativeThe terms False…
Continue ReadingA Guide to Machine Learning in R for Beginners: Logistic Regression
In the middle, around (0.3, 0.8), we’re correctly labeling about 80% of the poor care cases, with a 30% false…
Continue ReadingUsing mlr for Machine Learning in R: A Step By Step Approach for Decision Trees
Using mlr for Machine Learning in R: A Step By Step Approach for Decision TreesHyperparameter Tuning for optimizing performance.Asel MendisBlockedUnblockFollowFollowingNov 9I…
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