From space exploration to robotics, from game engines to medical research, and from training a single model to powering the entire data center, GPUs are an integral part of the process of how we deal with data.

If one thing that we need today, more than ever, is the speed to process the enormous data we generate. With the latest GTC 2020 keynote, which was delivered from the CEO’s kitchen, NVIDIA made clear that they want to utilize GPUs in all the fields possible.

In this article, we are going to learn how we can accelerate an end-to-end machine learning…

Working with and training large datasets, maintaining them all in one place, and deploying them to production is a challenging job. But what if I tell you there is a way to handle all of these with just a few clicks?

Let’s understand how we can do that easily. Throughout this article, we will create a dashboard (using Python and Voila) which runs a machine learning model to remove fraudulent transactions and displays remaining data with visualization, and publish it to Saturn Cloud’s production server for easier access. …

If you have stumbled upon/purposefully came to this article, I am presuming that you have a basic understanding of the Django structure and the framework in general. Therefore, skipping Django 101, I’ll straight dive into the main functionality.

The post is divided into two parts. Again, you may forward to the second half if you are already familiar with what template tags are.

Part 1 — Background of Django Template Tags

Part 2 — How to use Custom tags

Part 1 — Template Tags

The primary usage of template tags is to write some sort of code in your HTML so that it can display…

Python for Data Science

Update as on 26.02.2020 — FIFA somehow removed total data of the 2018 World Cup making this blog just for reference purposes. If I find the link of the archive somewhere, I’ll post it just under this. Apologies for the inconvenience in advance.

Most people think data science is about cool machine learning algorithms and self-driving cars. Let me tell you something, it’s not. Almost 80% of the time you are searching and cleaning the data, and if successful, remaining 20% in those cool stuff you see upfront.

“Find data and play with it” is the most repeated advice a…

But first, coffee.

The thing that stands true for most of us is we need coffee the first thing in the morning. Worldwide, with over 2.25 billion cups of coffee consumed on a daily basis, coffee is the second most traded commodity, falling a little short behind crude oil. No kidding. Let us understand how our favorite and world’s leading coffee chain Starbucks, with 17 million customers a week, plan their stores to get the most out of business.

Focusing on the right customer demographics and population plays an important role in the success of a business, but so does…

Data visualization is not merely science, it is an art. The way our human brain works, it is really easy to process information in the form of visualization. After almost 25 years into digital mapping and many companies using machine learning to collect mass amounts of data, data visualization is important more than ever.

In this article, we are going to visualize the Tesla Superchargers (charging stations) available at present in France. We will use Python, Folium, and Pandas to get the job done. Excited? Let’s get started.

First things First

Data

First things first, we are using Tesla Supercharger data by Government of…

It’s been a year since Google Dataset Search came out. Works like a charm but despite all the efforts, it’s still in its beta stage. And the aim of the article is to let you know how it works and how you can contribute to making it even better.

How many times do you search anything on Google on a given day? Maybe 10 times? or maybe over 100, depending upon your job, no one keeps a count. But our basic intuition to almost every question we don’t know is — “Google it”.

It’s same with the datasets, whenever we…

Let’s start with why.

Why do we need geospatial analysis? Why does it matter now more than ever?

Human brain recognizes information mostly based on time, date, and location. For example, “Remember we met yesterday at the theatre?” or “Where are you now?” followed by “I am at the university”.

With the help of today’s technologies — cellphones, GPS, social media, and more — one can collect geo-referenced (time and place) data of practically any event occurring around them, or even globally.

Geospatial analysis is leveraging this data into building maps, cartograms, statistics, and graphs, to show how changes are taking place and where…