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

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## 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…

Continue Reading## 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.…

Continue Reading## Principal Components of PCA

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

Continue Reading## 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…

Continue Reading## Visual Recognition using Graphs

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

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## Visualizing ELMo Contextual Vectors

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

Continue Reading## Saptashwa

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

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## 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;…

Continue Reading## 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”,…

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## 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…

Continue Reading## 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…

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