Customer feedback is great. But have you been able to turn that feedback into meaningful customer insights? A few years back, brands depended on surveys to gauge customers’ feelings about how their products were performing. From the product reviews, they were able to somehow get a grip on the general feeling of good, bad, or neutral response to their marketing campaign or product. There is, however, so much more information in the form of unstructured data that brands need to lay their hands on to better analyze the sentiments of their customers.Read More
AutoML refers to automated machine learning. It explains how the end to end process of machine learning can be automated at the organizational and educational level. Initially all these steps were done manually. The demand for machine learning is increasing day by day. Let’s see some of the most common AutoML libraries which are present in different programming languages.Read More
This blog marks the third entry in my ongoing “Teaching Tableau” blog. In our previous installments I showed how to create a basic dashboard from start to finish and how to work with filters. This week’s tutorial will go over “Calculations”.Read More
The first step in building a machine learning model is to prepare the data. This may involve pulling raw data from a variety of sources to load into a database. Likewise, the first step in cooking is to get the ingredients (the data). You may need to go to the grocery store to buy ingredients you don’t have at home (pull from a variety of sources).Read More
Representing statistical data in plain text or paragraphs, tables are pretty boring in my opinion. What about you? They become pretty difficult to understand and contrast. But, what makes them interesting and quite beautiful is the visual representation such as charts and diagrams.Read More
1. Show improvement relative to company KPIs. 2. Show incremental revenue impact.
3. Show cost reduction or time spent.
Thanks to the internet, now the world knew about the Presidential Debate 2020 that went out of control. All of the major news stations were reporting about how the participants were interrupting and sniping at one another.
I decided to put together an article that focuses on analyzing the words used in the event and see if there are any hidden insights.
Machine Learning is advancing steadily, enabling computers to understand natural language patterns and think somewhat like humans. The advances in Artificial Intelligence (AI) are increasing the prospects of businesses to automate tasks. With automation, you can save time and bring in more productivity for your business.Read More
Data analytics do not always require complicated programming. Applications can be achieved sometimes in a simpler way.Read More
In this Blog I am going to explain the way of how I learn the machine learning in 3–4 months comprehensively. So let’s get ready to dive into the journey of ML.Read More
Let’s now look at some of the useful sites for finding open and publicly available datasets, quickly and without much hassle.Read More
The model should conform to these assumptions to produce a best Linear Regression fit to the data.Read More
Until 2015, even professional programmers didn’t consider machine learning has real potential and benefits. However, with innovation the development of AI and computing capabilities build-up, autonomous MLOps platforms began to develop rapidly and became an integral part of computer systems development.Read More
Machine learning papers are notorious for creating dozens of variables and expecting the reader to know what they mean when they are referenced later. Take a highlighter and highlight where a variable is ‘initialized’ and where it is used henceforth. This will make reading much easier.Read More
We will use seaborn’s dataset on tips to exemplify my tips.Read More
Data leakage in machine learning pipelines can cause havoc for your model. In this post, I’m going to share an amazingly simple way to detect data leakages using NANs and complex numbers while treating your ML pipeline as a black box.Read More
Relational operators help us see how objects relate to one another.Read More
Credit card frauds are a “still growing” problem in the world. Losses in frauds were estimated in more than US$27 billion in 2018 and are still projected to grow significantly for the next years as this article shows.Read More
Although the built-in functions of Pandas are capable of performing efficient data analysis, custom made functions or libraries add value to Pandas. In this post, we will explore one of these add-ons which is sidetable.Read More
Data Scientist vs Data Analyst interview. Here’s the difference.Read More