I recently started using DataBricks more frequently in the past 2 months, and I have had many mood swings about it. One minute I am super impressed, and the other minute, I abhor it. To be fair, a lot of the negative emotions about it can be linked to the fact that it needs some getting used to, and I find myself lacking the time to do that.
But what is DataBricks?
In simple terms, DataBrick is like Jupyter notebook but so much more and on steroids. It trumps Jupyter notebook in terms of
Visualization is one of the cores of data analytics. It is one of my favourite part of analytics because it challenges your communication skills and is the most user-centric part of the analysis.
Even though my default programming language is python. It is not my favourite tools for visualization: Tableau takes that position. And for over a year, I have been consciously taking to improve how I convey information through visualization using Tableau most of the time.
If you check my Tableau profile, you will immediately realize that I am nowhere near perfect, and I still make a s**t load…
I know, I know. The book has a cheesy title. At least that was my first impression. I assumed it was a marketing gimmick book with a “clickbait” title that would have very fluffy assumptions as content. If not because a trusted source recommended this book, I probably would not have been “caught dead” reading it. As they say, do not judge a book by its cover.
For one thing, the entirety of this book confirms the two things I am beginning to understand
For me, this book…
As 2020 draws to its ends (hopefully along with its chaos), I took a step back to reminisce about all the tools/skills I have picked up this year and all the tools I really didn’t use so much this year. One tool I really didn’t use so much is Tableau.
Tableau is a powerful data visualization tool that creates visually-appealing dashboards.
I decided to find a dataset to analyze and visualize on Tableau.
One tool that I picked up this year and I have used quite frequently is Streamlit.
Streamlit is such an awesome tool for data scientists.
I recently discovered that I retain more information when I read a book in audio format than in written format. This discovery instigated the need to find ways to read Medium posts in audio formats like a podcast. My first plan was to gather all my medium read lists and convert them to audio. Unfortunately, Medium API technically does not support this. What it does support, however, is getting article feeds by username. Therefore I decided to streamline my goal, for now, to convert one of my old medium posts to audio. Here is the sample below
Amazon Web Services (AWS) is one of the market leaders in cloud computing. It has lots of services, ranging from infrastructure as a service (IAAS) to platform as a service (PAAS) and some software as a service (SAAS).
AWS services can be accessed in two ways: via the GUI (the AWS management console) and programmatic access via API, CLI, SDK, etc.
For this article, we will be focusing on setting up the CLI interface.
There are two major benefits of using the AWS CLI interface:
With the increasing global interest in cloud computing and its potential benefits across business sectors, Amazon Web Services (AWS) seems to be the popular term in people’s minds. This may be because AWS is the fastest and biggest public cloud provider in the world having business customers in over 190 countries and more than a million active users. It is a leader in the Gartner Magic Quadrant for cloud infrastructure as a Service (IaaS) for nine consecutive years and recently, also the leader for cloud platform as a service (PaaS).
Before diving deeper into AWS, let’s understand what cloud computing…
Before getting started, please note that this topic would be most beneficial if you know and understand Python classes. Here’s a helpful primer on that topic:
Python magic methods are also known as dunder methods or special methods. But why such dramatic names? They’re used to overwrite or emulate the behavior of built-in functions.
They’re also easy to recognize, as they follow a particular pattern: They have double underscores as prefixes and suffixes. Hence, the name dunder means Double Underscore. They’re referred to as special methods because they add “magic” to your python classes. Common examples are
Like a lot of people also transitioning to Data Science from a Non-technical background, I officially kickstarted my Data Science Career as a Junior Data Scientist …in May to be precise.
Honestly, I have no regrets so far especially because of my passion for the field and the amazing team I joined that is a good culture fit for me.
Far from my expectation, I jumped into an active work project on my day 2 at the job. This meant I got exposed to both the non-technical workflow and technical workflow at the same time. …
I stopped journaling for so many reasons, but one major reason trumped them all: I felt journaling had to be something serious where I have to spend quality time daily to write out something structured and perfect. As my daily schedule became more and more complex, I didn’t see a future of it along with other serious things in my life that struggled for my time.
At the moment when I am writing this, it is April 2020. This means I am currently in self-isolation due to the COVID-19 crisis. As much as this crisis comes with a lot of…
Data Scientist | Building Data Product with Python, Analytics, and Machine Learning | New Technologies Obsessed| Self-care Conscious