# Technical Skills Archive

## Coding principles for rapid machine learning experimentation

According to François Chollet, the creator of Keras and Someone who at his best, placed 17th on Kaggle’s cumulative leaderboard: it is not about having the best idea(s) from the start but rather iterating over ideas often

## How can I solve any question on finding the probability of an event in a job interview / written test? (Part 2)

Properties of probability i) 0 ≤ P(A) ≤ 1. ii) P(ɸ) = 0, P(S) = 1. iii) For any two events A and B, P(AUB) = P(A) + P(B) – P(A∩B), where AUB is read as ‘A

## Web Scraping using Selenium

What is Web Scraping? Web Scraping is a popular methodology to extract data from websites. This is often done to derive insights for Sentiment Analysis, Predicting User preferences, Cross-Selling products, etc. Some of the real-life examples of

## Outlier Detection in High Dimensional Data using ABOD

We know what outliers are – the data points that lie outside of where most of our data lie. When dealing with Outliers, it is relatively straightforward to find outliers in a uni-dimensional setting where we could

## All the Numbers Behind the Decision Tree

In this article, we are going to see various numbers which we get as output after we implement a decision tree. Prerequisite Before you can start reading this blog we expect you to have these prior understanding

## Outlier Detection in Time Series

Anomalies a.k.a Outliers are patterns in data which do not conform to the data points near to it.  Statistically, they are the data points that are deemed to belong to a different population. Timely detection of anomaly

## Multi-Label Classification

Classification has been a go-to approach for various problems for many years now. However, with problems becoming more and more specific a simple classification model can’t be the solution for all of them. Rather than having one

## How to use ELMo Embedding in Bidirectional LSTM model architecture?

Embeddings from Language Models (ELMo) ELMo embedding was developed by Allen Institute for AI, The paper “Deep contextualized word representations” was released in 2018. It is a state-of-the-art technique in the field of Text (NLP). It is

## Handling Class Imbalance – An Ensemble – Majority Voting on Minority Samples

Class Imbalance is a major problem in machine learning models where the total number of one class data is far less than the total number of another class. This problem is extremely common in practice and can

## Introduction to All-Inclusive Architecture

If we have a huge amount of structured data, numerical or categorical, a simple neural network architecture can give amazing results. A CNN architecture can take care of Image data and a simple RNN or LSTM architecture