Design Psych.

Principles used in Human-Computer Interaction (HCI) Studies

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Image by the Gerd Altmann.

A year back, I got an opportunity to read Human-Computer Interaction(HCI) at my university. …


1 + 1 = 3

Stripping Away The Excess

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Some of The Extracts of 2020 Ironvizzes. Viz By The Respective Owner, Image Source From The Blog of Will Sutton.

A few months back, while I was surfing Instagram, I saw a comment in a post, with a remark, “You have used data-ink ratio in good order.” I immediately started exploring the term “data-ink” and realized that it was coined by “Edward Tufte.” I had read his name on some of the research papers a few months ago on the Human-Computer Interaction course. As I determined the connection between the author’s name and the term data-ink ratio, I began to explore it and started implementing it on my data visualization journey.

This blog is dedicated to those who want to dive into or are engaging in mesmerizing data visualization fields. …


An Approach with Artificial Intelligence Concepts

Detailed Report For Developing Spam or Ham Classifier: Part 3

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Designed with Canva. Illustration from unDraw.

TL;DR Understanding spam or ham classifier from the aspect of Artificial Intelligence concepts, work with various classification algorithms, and select high accuracy producing algorithms and develop the Python Flask App.

The blog is a series of the blog post, if you haven’t read the theoretical Artificial Intelligence concept of spam or ham classifier and have not worked with algorithms in jupyter notebook, please explore it at:

We have covered in part 1 & 2

  • Theoretical AI Concept Regarding Spam or Ham Classifier
  • Classification Algorithms
  • Exploring Data Source
  • Data Preparation
  • Exploratory Data Analysis

We will cover here in Part 3

  • Naïve Bayes Behind Spam or…


An Approach with Artificial Intelligence Concepts

Detailed Report For Developing Spam or Ham Classifier: Part 2

Image for post
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Designed with Canva. Illustration from unDraw.

TL;DR Understanding spam or ham classifier from the aspect of Artificial Intelligence concepts, work with various classification algorithms, and select high accuracy producing algorithms and develop the Python Flask App.

The blog is a series of the blog post, if you haven’t read the theoretical Artificial Intelligence concept of spam or ham classifier, please take a ten-minute read at:

We have covered in Part 1

  • Theoretical AI Concept Regarding Spam or Ham Classifier
  • Classification Algorithms

We will cover here in Part 2

  • Exploring Data Source
  • Data Preparation
  • Exploratory Data Analysis

We will cover in next Part 3

  • Naïve Bayes Behind Spam or…


An Approach with Artificial Intelligence Concepts

Detailed Report for Developing Spam or Ham Classifier: Part 1

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Designed with Canva. Illustration from unDraw.

TL;DR Understanding spam or ham classifier from the aspect of Artificial Intelligence concepts, work with various classification algorithms, and select high accuracy producing algorithm and develop the Python Flask App for SMS: spam or ham detector.

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Final product. Gif by Author.

Short Message Services (SMS) is far more than just a technology for a chat. SMS technology evolved out of the global system for mobile communications standard, an internationally accepted[1]. Spam is the abuse of electronic messaging systems to send unsolicited messages in bulk indiscriminately [2]. While the most widely recognized form of spam is email spam, the term is applied to similar abuses in other media and mediums. SMS Spam in the context is very similar to email spams, typically, unsolicited bulk messaging with some business interest. SMS spam is used for commercial advertising and spreading phishing links. Commercial spammers use malware to send SMS spam because sending SMS spam is illegal in most countries. Sending spam from a compromised machine reduces the risk to the spammer because it obscures the provenance of the spam. SMS can have a limited number of characters, which includes alphabets, numbers, and a few symbols. …


Data Matching, Fuzzy Matching, Data Deduplication

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Name Matching Problem Sneak Peek, Image by Author.

Recently I came across this dataset, where I needed to analyze the sales recording of digital products. I got the dataset of having almost 572000 rows and 12 columns. I was so excited to work on such big data. With great enthusiasm, I gave a quick view of data, and I found the same name repeatedly taking different rows. (Ah! Much time for data cleaning!).

On some product column, it contains iphone while on other it was written Iphone, or iphone 7 + and iphone 7 Plus, and for some regular customer list, some have Pushpa Yadav while on other Puspa Yadav (the name is Pseudo). …


Correlation does not prove Causation!

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The “chicken or egg” paradox was first proposed by philosophers in Ancient Greece to describe the problem of determining cause-and-effect. Photo by Katherine Chase on Unsplash

TL;DR: Correlation does not necessarily mean causation! See yourself through this Infographic.

“Correlation does not prove causation”: This was the statement I came across during my Udacity-Bertelsmann Technology Scholarship on Data Track Course- 2019. I was awestruck by this line. I was doing EDA, and based on correlation; I summed up my result(causation accepted). [Yes, I was wrong!]

That very line from Bertelsmann Data Track course made me realize that I was steering towards wrong analysis; thus, I started to dig deeper and try to understand the thin line difference between Correlation & Causation.

Understanding the phrase “Correlation does not prove causation” and underpinning the concept on your next data science project will make you double confident. …


Secret Sauce for EDA

Data is nothing until you understand it and visualize it most effectively and this is what we call Exploratory Data Analysis(EDA)

EDA cycle: Understanding data quality, description, shape, patterns, relationships, and visualizing it for better understanding. Read more about EDA.

Pandas is a Python library that provides extensive means for data analysis. …


Excellent program for data detox

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Life is all about balancing. Photo by: Matthew Henry

We are submerged with devices that hold a lot of data we shared. I don’t have glass in view of what my data does and who holds power using my data, Then I found Data Detox.

Detoxification: Process of removing toxic substance or qualities

Data: facts/qualities.

So Data Detox is the process of tidying up my data.

First, it looks like eight days long-scheduled course but NO — it is more than a course:

It is more about exploring and cleaning my digital/virtual life and same time enjoying my digital life.

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Info About the Program

Name: Data Detox Kit

Designed by: (Nonprofit groups) Mozilla and the Tactical Technology…

About

Mala Deep

Data Science | Data Visualization | Community Work Focused | Philekoos | https://www.linkedin.com/in/maladeep/

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