Source : Unsplash

“Logistic Regression is not Regression but a Classification Algorithm”.

You might have seen this in latest popular machine learning books, blogs or you might have heard *Data Science Gurus* utter the same in their highly subscribed YouTube channels.

Machine learning has usurped and renamed many statistical techniques. Often to the extent that they now disbelieve and reject its statistical origins. Case in point is “Logistic regression is not Regression”

However, nothing can be further from the truth than this assertion. We live in a meme culture, memes even become cryptocurrency.

So why not use a meme to drive home the…


Source: Unsplash

“Logistic Regression is not Regression but a Classification Algorithm”.

You might have seen this in latest popular machine learning books, blogs or you might have heard *Data Science Gurus* utter the same in their highly subscribed YouTube channels.

Machine learning has usurped and renamed many statistical techniques. Often to the extent that they now disbelieve and reject its statistical origins. Case in point is “Logistic regression is not Regression”

However, nothing can be further from the truth than this assertion. We live in a meme culture, memes even become cryptocurrency.

So why not use a meme to drive home the…


Image Source: Pixabay

If the words ‘Dynamic Time Warping’ evokes a sense of time travel science fiction, you would not be at fault.

So let us first unpack this science fiction terminology.

Dynamic Time Warping

Dynamic Time Warping (DTW) is a time series analysis technique used for measuring similarity between two temporal sequence. These sequences or time series could be of different length as well.

It calculates the optimal match between two series using a set of rules. Suppose there are two series — A and B. …


Image Source: Pixabay

If the words ‘Dynamic Time Warping’ evokes a sense of time travel science fiction, you would not be at fault.

So let us first unpack this science fiction terminology.

Dynamic Time Warping

Dynamic Time Warping (DTW) is a time series analysis technique used for measuring similarity between two temporal sequence. These sequences or time series could be of different length as well.

It calculates the optimal match between two series using a set of rules. Suppose there are two series — A and B. …


Or which forecast accuracy metrics to use?

Source: https://www.arymalabs.com/

Many CPG brands across the world would be focusing on keeping a tab on their sales and demand numbers during the Covid-19 pandemic. In my previous article, I had covered points on doing Marketing Mix modeling during these testing times.

The brands might have already forecasted sales or demands for the first 3–4 months of 2020. But what could have been missed from their forecasts is the effect of Covid-19.

With the increase in sales being reported by many brands, the forecasted sales would be way off the mark and there would be a huge divergence in the forecasted sales…


Covid-19 has brought misery to the world, many lives have been lost, cities wear a deserted look and economies are on the verge of collapse.

Source: https://www.businessinsider.com/

At this point of writing this article there were 2,444,614 number of cases (1,636,267 active cases) worldwide and 168,005 number of deaths.


Source

Introduction

The objective of the exercise was to identify hostile topics emerging out of social media data. four Data sources were analysed for the given exercise: Facebook, Instagram, YouTube and Twitter. Topic Modeling and other Natural Language Processing algorithms were used to identify several topics from social media posts and comments, across different geographies for a specific time period.

Topic models are a family of statistical-based algorithms to summarize, explore and index large collections of text documents.1 Latent Dirichlet Allocation approach was used to identify several topics emerging out of social media conversations.

This case study would entail methodology followed…


Source: Pixabay

Digital advertisement spends are surpassing traditional ad spends (TV, print, outdoor). Most brands have shifted focus on targeting customers directly through various digital platforms to get a larger share of the sales pie.

Digital campaigns help in targeting customers at a more personalized level. An effective digital strategy involves focus on good quality content and targeting the right audience. But the key factor in nailing the right strategy is to understand which mediums and campaigns worked the best and formulating the right mix of channels for the future. …


Get to know your customers’ next move through Markov Chain

Image Source : http://setosa.io/ev/markov-chains/

Imagine you are a company selling a fast-moving consumer good in the market.

Let’s assume that the customer would follow the below journey to make the final purchase:


Source: www.mstecker.com/

Clustering is an unsupervised technique which classifies certain objects into groups called Clusters such that the objects within one cluster have similar pattern and have distinct pattern as compared to objects in other clusters.

Market Segmentation using clustering analysis helps in dividing various markets into small buckets based on the similarity or uniqueness in customer behavior and other aspects. Some of the characteristics include price point of different brands, market share of brands, demographics (age, gender, income), behavioral (usage, frequency, loyalty), geographical, propensity, media habits etc.

In this article, I will present a small case study on how k-means can…

Ridhima Kumar

Founder- Aryma Labs; Expertise in Marketing Mix Modeling, Forecasting, ML and NLP. Avid Reader.

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