Hyper-Parameter Tuning and Model Selection, Like a Movie StarCoding, analyzing, selecting, and tuning like you really know what you’re doing. Caleb NealeBlockedUnblockFollowFollowingJun…

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## 1st Place Solution for Intel Scene Classification Challenge

1st Place Solution for Intel Scene Classification ChallengeHosted by Analytics VidhyaAfzal SayedBlockedUnblockFollowFollowingJun 2IntroductionProblemYou are provided with a dataset of ~25k…

Continue Reading## How Twitter and Machine Learning (KDE + LDA) help to predict Crime?

He (Gerber) uses, in addition to KDE, topic modeling on these messages, in particular LDA. As a brief summary, LDA…

Continue Reading## Layman’s Introduction to KNN

Layman’s Introduction to KNNk-nearest neighbour algorithm is where most people begin when starting with machine learning. Rishi SidhuBlockedUnblockFollowFollowingMay 20Photo by timJ…

Continue Reading## Why Measuring Accuracy Is Hard (and important!) Part 2

What if I use this split instead:The naive way might be just to shuffle your dataset randomly and split it…

Continue Reading## Why measuring accuracy is hard (and very important)!

We find some acceptable point on the ROC curve, set the threshold to that point, and use these two new…

Continue Reading## Extremely Imbalanced data — Fraud detection

This is because we can predict all the isFraud=0 cases perfectly, but none of the isFraud=1 cases. So out of…

Continue Reading## Review: CRF-RNN — Conditional Random Fields as Recurrent Neural Networks (Semantic Segmentation)

Review: CRF-RNN — Conditional Random Fields as Recurrent Neural Networks (Semantic Segmentation)An Approach Integrating CRF into End-to-end Deep Learning SolutionSH TsangBlockedUnblockFollowFollowingMar 3In this…

Continue Reading## Python Data Science Getting Started Tutorial: NLTK

The combined classifier algorithm is a commonly used technique, which is implemented by creating a voting system. Each algorithm has…

Continue Reading## Machine learning with the “diabetes” data set in R

Machine learning with the “diabetes” data set in RClassification with KNN, logistic regression, and decision treesWilliam ButlerBlockedUnblockFollowFollowingJan 17Inspired by Susan Li’s article…

Continue Reading## Logistic Regression Model Tuning with scikit-learn — Part 1

Logistic Regression Model Tuning with scikit-learn — Part 1Comparison of metrics along the model tuning processFinn QiaoBlockedUnblockFollowFollowingJan 8Classifiers are a core component of machine…

Continue Reading## Impact of Dataset Size on Deep Learning Model Skill And Performance Estimates

We will define a model that performs well on this dataset as a model that has effectively learned the two…

Continue Reading## How to Reduce the Variance of Deep Learning Models in Keras Using Model Averaging Ensembles

The model then has a single hidden layer with 15 modes and a rectified linear activation function, then an output…

Continue Reading## Text Generation Using Recurrent Neural Networks

It has an average accuracy of 0.6245 and loss of 1.25 over 5 randomly sampled test sequences.Yes, but to talk…

Continue Reading## A Guide for Building Convolutional Neural Networks

Before that, you’re just experimenting and prototyping and so there’s no need to make your training time longer by having…

Continue Reading## How I improved a Human Action Classifier to 80% Validation Accuracy in 6 Easy Steps

The ensemble achieved a validation accuracy of 0.821 which is a significant improvement from the baseline paper’s accuracy of 0.672.Background…

Continue Reading## Holy Grail of AI for Enterprise — Explainable AI

In reality, Customers are the less bothered accuracy of AI model, but their concerns are about Cluelessness of Data Scientist…

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