# vector

## What Is Argmax in Machine Learning?

Argmax is a mathematical function that you may encounter in applied machine learning. For example, you may see “argmax” or…

## Support Vector Regression Tutorial for Machine Learning

Unlocking a New World with the Support Vector Regression Algorithm Support Vector Machines (SVM) are popularly and widely used for…

## How to plot the spiral of Theodorus

At each step, you need to draw a segment of length 1, perpendicular to the hypotenuse of the previous triangle.…

## Principal Components of PCA

Recall that covariance is only between 2 dimensions, therefore the result is a covariance matrix. It is useful to know…

## Beginning with R — The uncharted territory

Beginning with R — The uncharted territoryPuneet SharmaBlockedUnblockFollowFollowingJul 3Coming from a non-programming background and python being the first exposure to programming and…

## Visual Recognition using Graphs

No, right. We need a feature representation of each object present in the image that separates it from other objects…

## Anki Vector SDK: A robot with attitude

Well, as Vector owners around the world waited for their trusty companion to take it’s last beeps, Anki released a…

## SVM: Feature Selection and Kernels

(Source: https://towardsdatascience. com/support-vector-machine-vs-logistic-regression-94cc2975433f)SVM: Feature Selection and KernelsPier Paolo IppolitoBlockedUnblockFollowFollowingJun 2A Support Vector Machine (SVM) is a supervised machine learning algorithm that…

## Visualizing ELMo Contextual Vectors

Visualizing ELMo Contextual VectorsContextual vectors can be useful for word sense disambiguation. Henry ChangBlockedUnblockFollowFollowingApr 15Issue with Word EmbeddingThere are difficulties…

## Saptashwa

Data Handling Using Pandas: Cleaning and ProcessingMastering Pandas to Deal with ‘Dirty Data’Learn Python from the Fake Album Covers GameWeb Scrapping, String…

## Principal Component Analysis — Math and Intuition (Post 2)

Principal Component Analysis — Math and Intuition (Post 2)Shivangi PatelBlockedUnblockFollowFollowingApr 4This is Post 2 of a 3-part series on Principal Component Analysis — Math and…

## Visual Agnosia: A Neural Network Analogy

Visual Agnosia: A Neural Network AnalogyAryan SinghBlockedUnblockFollowFollowingMar 25Visual Agnosia: Intricate Brain ImbroglioThis week I began reading Dr. Oliver Sacks’s story, The…

## Machine translation from scratch with MXNet and R

With an attention mechanism, the data feeding the decoder is now the entire encoded sequence, solving the information bottleneck of…

## A Practical Look at Vectors and Your Data

But in order for R² to be called a vector space, you must verify that it follows all the rules;…

## Sentiment Analysis with Deep Learning of Netflix Reviews

This is where we use the word-to-index map. Consider you want to get the embedding vector for the word “although”,…

## R: rank vs. order

R: rank vs.  orderRebecca PeltzBlockedUnblockFollowFollowingJun 12, 2018If you’re learning R you’ve come across the sort, rank and order functions. Because…

## Marco Peixeiro

End to End Time Series Analysis and ModellingApply moving average, exponential smoothing, and SARIMA…Almost Everything You Need to Know About Time SeriesUnderstand…

## How companies use collaborative filtering to learn exactly what you want

Whether it’s that new set of speakers that you’ve been eyeballing, or the next Black Mirror episode — their use of predictive…

## How to Avoid Exploding Gradients in Neural Networks With Gradient Clipping

Training a neural network can become unstable given the choice of error function, learning rate, or even the scale of…

## 10 not so intuitive things about programming with R

10 not so intuitive things about programming with RJyoti Prakash MaheswariBlockedUnblockFollowFollowingAug 18, 2018Why Use R for Data ScienceR has traditionally been regarded…

## Getting Started with Randomized Optimization in Python

Getting Started with Randomized Optimization in PythonHow to use randomized optimization algorithms to solve simple optimization problems with Python’s mlrose packageGenevieve HayesBlockedUnblockFollowFollowingJan…

## Understanding how to explain predictions with “explanation vectors”

Understanding how to explain predictions with “explanation vectors”Pol FerrandoBlockedUnblockFollowFollowingJan 10In a recent post I introduced three existing approaches to explain…

## What Kagglers are using for Text Classification

Moreover, the Bidirectional LSTM keeps the contextual information in both directions which is pretty useful in text classification task (But…