Formula 1 Racing Visualization (Part 2) — Constructor and Driver

Formula 1 Racing Data Visualization (Part 2) — Constructor and DriverPhoto by Mika Baumeister on UnsplashSince 1981, Formula One teams have been required to build the chassis in which they compete, and consequently the terms “Team” and “Constructor” became more or less interchangeable.In any case you missed Part 1 of Formula 1 Racing Visualization(click...

15h

A Simple Code to Read 1.2 Billion Rows Just in 1 Second

Read and Visualize 1.2 Billion Rows of Galaxy Simulation Data EffectivelyContinue reading on Analytics Vidhya »

18h

A Detailed Study of Self Supervised Contrastive Loss and Supervised Contrastive Loss

A deep dive into supervised contrastive lossIntroductionSupervised Contrastive Learning paper claims a big deal about supervised learning and cross-entropy loss vs supervised contrastive loss for better image representation and classification tasks. Let’s go in-depth in this paper what is about.Claim actually close to 1% improvement on image net data set¹.Classification...

18h

6 GAN Architectures You Really Should Know

Source: neptune.aiThis article was originally written by Shibsankar Das and posted on the Neptune blog.Generative Adversarial Networks (GANs) were first introduced in 2014 by Ian Goodfellow et. al. and since then this topic itself opened up a new area of research.Within a few years, the research community came up with plenty of papers on this topic...

18h

How does Self Organizing Algorithm works?

A simple step- by-step guide with mathematical exampleContinue reading on Analytics Vidhya »

18h

Twitter Bot 101 : Part#1

Twitter Bot 101 : Part#1The social media platforms today contain so many bots than any of us is mindful of.Talking about the bots on social media, Twitter is one of the most popular platforms for deploying and managing bots.Today, let us take a look at how these Twitter bots can be created and run to perform tasks like auto-reply, auto-like and auto-retweet....

18h

Sentiment Analysis with Vader and Algorithmic Trading

Photo by Stephen Dawson on UnsplashSentiment analysis has gained relevance lately as it is in the case of analysis of Twitter posts, this is based on the analysis of texts in which a positive or negative sentiment is assigned according to the words that a certain phrase or text contains. This analysis combines the use of Natural Language Processing...

18h

How to scrape thousands of adoptable pet photos from Petfinder using Petpy API: Part 1 —…

How to scrape thousands of adoptable pet photos from Petfinder using Petpy API: Part 1 — Gathering pet dataWhile working on my Capstone, using the Petpy API and following along with Aaron Schlegel’s instructions on how to download 45,000 adoptable cat images with petpy, I ran into a few trouble spots when trying to use some of the attributes. I realized...

18h

How to scrape thousands of adoptable pet photos from Petfinder using Petpy API: Part 2—…

How to scrape thousands of adoptable pet photos from Petfinder using Petpy API: Part 2— Downloading pet imagesRecall in part 1, we left off with a cleaned dataframe containing the pet’s id, the breeds and the photos. The next step would be to decide which photos we want to download.We need our imports first.import petpyimport osimport pandas as pdimport...

18h

Hello World of Computer Vision: MNIST handwritten digit classification

Photo by Pop & Zebra on UnsplashIn this story, we will be tackling the legendary MNIST dataset. This dataset is quite popular among Machine Learning beginners. In fact, this data set is so popular that it is often termed as “Hello World” of Machine Learning or Computer Vision.This story will also give an idea about classification problems in machine...

18h