Coastal Econometrician Views

Campaign Data to Qualified Lead (Scoring)

2023-01-17T13:36:00.000+05:30

In recent times, almost all organizations run campaigns (though they differ in their size, channel, type, audience, etc.,) all are aimed either loosely or strictly for demand generation in short/long term. Now due to variety, veracity and variability of such campaigns, campaign data lacks a unified view that can straightforwardly provide the set of metrics or values that are needed for

This Recession, put your data to work with help of Data Sciences

2022-11-07T11:55:00.002+05:30

Nearest Neighbourhoods for forecasting of Fast Moving Consumer Goods (FMCGs)

2022-09-29T18:42:00.003+05:30

Customer Recent Reviews and Impact on Purchase Decision

2022-03-29T12:40:00.002+05:30

In recent times after covid-19 waves, business in MELT (Media, Entertainment, Leisure, and Travel) are re-starting or re-picking up their business. However, this business has lot of dependency on the social media reviews, that too on latest ones. This study just summarized how recent reviews about the Leisure and Travel effecting purchase decision of their customer.

Avoid Blind Supply Chain Practices during Covid-19 Crisis Times

2020-10-16T15:22:00.005+05:30

Getting Started with Data Science Brain Teaser Document

2020-10-12T11:06:00.007+05:30

https://github.com/pradeepmav/Getting_Started_with_DS_Brain_Teaser_DocPDF Doc Link: https://github.com/pradeepmav/Getting_Started_with_DS_Brain_Teaser_Doc/blob/main/Jumping_into_DS_with_R_Python.pdf

Tip (4), Variable Explorer for both R and Python in RStudio

2020-07-01T18:43:00.000+05:30

In recent past, frequent usage of both R and Python by Data Scientists are considerably increasing. RStudio is preferred IDE for most of R users, though, there are Editors and Notebooks which serve for both languages, yet, switching between them is not easy. Especially for those who got used to RStudio "Environment" tab for exploring objects in current

COVID-19 Testing in India – Retrospectively, seems like tested more wrong samples.

2020-04-09T11:55:00.002+05:30

Author's view are personal and from his professional experience. mavuluri.pradeep@gmail.com

Tip (3), Arrow, columnar (binary file) formats for both R and Python

2020-02-16T23:02:00.002+05:30

Though Arrow was for around from some time (more than a year), in its recent release they came up with compression support that makes it be more user friendly for all data science activities across different languages. In my earlier posts, I have encouraged R users to use fst, however, in recent days, as Data Scientists frequency use both R and Python, an effective small files that can be easily

Tip (2) for R to Python and Vice-Versa seamlessly

2019-12-16T15:30:00.000+05:30

In continuation to my earlier R to Python tips, in order to deal with both Python and R simultaneously for client requests; this time with respect to plots where both schools as of now by large distinct in their plotting styles; Plotnine a new python package for grammar of graphics will help us with ease for two language enthusiasts. Plotnine which is almost in same style (> 90%) as

Machine Learning (ML) helps in not wasting time in non responsive telemarketing calls

2019-11-22T18:24:00.000+05:30

My last year post was more about how ML helped in identifying best time for telemarketing calls. This one on not wasting time in non responsive telemarketing calls. Views expressed here are from author’s industry experience. Author trains on and blogs Machine (Deep) Learning applications; for further details, he will be available at mavuluri.pradeep@gmail.com for

SKU Level Forecasting: Understanding Sales Segements

2019-11-03T16:05:00.000+05:30

Understanding you sales segments especially when they are available at SKU level will help us achieving better forecasts. Look for following first, instead of reverse engineer with ML/Statistical techniques and wasting time in front. 1) Sales Variation - Foremost thing one should follow when we have SKU level data is to look for each SKU variability with respect to their average sales or

Repetitive Q: Reading Multiple Files in the Zip Folder

2019-10-17T12:36:00.000+05:30

Dear Readers, I always see a repetitive question coming to me and across various forums on how to read multiple files in the zip folder of same separator or multiple separator. Again, here, lets not compromise on speed. Solution is to use easycsv package in R, which in turn uses data.table package function "fread". Find below a quick example: library(easycsv) ## Loading required package:

Forecast Stability Guidance for Model Selection

2019-10-03T11:29:00.000+05:30

In real world forecasting task, we don’t have luxury of actuals in hand for better model selection, in such realistic situations, forecast stability can guide us to some extent. Forecast Stability in simple terms, is all about how forecasts behave versus forecasts, we can measure it with simple coefficient of variation. This measure also helps us to understand non-randomness across the data. When

Forecast Stability Guidance for Model Selection

2019-10-01T23:37:00.000+05:30

Forecast Stability Guidance for Model Selection /*! jQuery v1.11.3 | (c) 2005, 2015 jQuery Foundation, Inc. | jquery.org/license */ !function(a,b){"object"==typeof module&&"object"==typeof module.exports?module.exports=a.document?b(a,!0):function(a){if(!a.document)throw new Error("jQuery requires a window with a document");return b(a)}:b(a)}("undefined"!=typeof

Case Study: How Machine Learning Helps Seasonal Delivery

2019-09-26T18:16:00.000+05:30

Views expressed here are from author’s industry experience. Author trains on and blogs Machine (Deep) Learning applications; for further details, he will be available at mavuluri.pradeep@gmail.com for more details. Find more about author at http://in.linkedin.com/in/pradeepmavuluri

Finite Life Cycle - Fast Moving (Tech) Consumer Goods Demand Behavior

2019-09-10T21:00:00.003+05:30

In today’s tech world, few products being introduced into the market that have a finite (or limited) life cycle with new features from time to time in order to show case their innovations or for brand enhancement. So, how does their sales/demand cycle look alike and what manufacturers need to understand about their demand behavior/forecasts. Towards the same, first one need to understand

Tips for R to Python and Vice-Versa seamlessly

2019-03-31T17:26:00.000+05:30

When we TATVA AI visit our clients, often both data scientists and higher management ask us, how we deal with both Python and R simultaneously for client requests; as there is no universal preference among clients. Though solution is not straight forward, however, I suggest to exploit common libraries for quick deployments, such as, dfply (python) and dplyr (R). Below is a quick

Record Linkage, Entity Matching, Data De-Duplication, when free, why paid services?

2019-03-27T16:21:00.000+05:30

Recurrence of records that refer to same values / entities across different data bases is a concern in modern data age; as they are not ready for next level of analysis and criticized for creating noise in the models. The task of finding or cleaning such tasks are known as record linkage, data matching, entity resolution, etc., assumed importance from past few decades. One can find here,

Nimble tweak to use specific python version or virtual environment in RStudio

2019-01-01T23:28:00.000+05:30

Reticulate made switch between R & Python easy, and doing its best to facilitate both worlds of data science. Meanwhile, I noticed that most of my followers or students raised the issues of uneasy switch between different python versions or virtual environments in RStudio while using repl_python(). Here is my nimble tweak, hope, RStudio will come up with a better solution in coming days

ML helps in identifying best Day & Time for telemarketing calls

2018-12-25T21:26:00.001+05:30

High Frequency Forecasting - Pragmatic Confessions

2018-12-18T18:44:00.000+05:30

Views expressed here are from author’s industry experience. Author also trains on Machine (Deep) Learning applications; for further details, he will be available at info@tatvaai.com or mavuluri.pradeep@gmail.com for more details. Find more about author at http://in.linkedin.com/in/pradeepmavuluri

Attrition Percentage By Reason @ Online Delivery (Boys) Business

2018-12-12T19:36:00.000+05:30

For more details, reach at either info@tatvaai.com or mavuluri.pradeep@gmail.comFind more about author at http://in.linkedin.com/in/pradeepmavuluri

Detection of Lazy Delivery Boys using IoT Data and ML

2018-12-03T20:50:00.000+05:30

TATVA AI Discussion Room

2018-12-01T16:15:00.000+05:30

TATVA AI engages a dedicate discussion room for all future white board discussions, and place of contact near Kundalahalli Gate, Bengaluru-66. Interested can drop in with prior appointment. info@tatvaai.com or mavuluri.pradeep@gmail.com