Using Python with VBA to automate Microsoft Excel Workflows

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In this age of Data, python has become the most widely adopted language by many developers around the globe. This means that there are many potential libraries sitting there waiting to be utilized.

While python has recently gained the ethos for being the first choice to analyze data and has a very wide spectrum of applications spanning low to heavy usage for many tasks; Microsoft Excel has a history of, and in most cases still is an inevitable tool used to analyze/munge/visualize data.

Imagine if we could utilise the open-source libraries which are available in python for automating our workflows…

Anime Face Recognition with Deep Learning


I have had been meaning to study an area of deep learning called metric learning and I figured out a great learning use-case that piqued my interest and made me delve straight into it. It’s the face recognition problem.

But wait, there’s a slight twist here. We’re not doing plain human facial recognition because it’s just meh, very commonplace!. As a proponent of the otaku culture, I thought let’s do facial recognition with anime characters!!

This would be a three post series which would talk about every aspect of the project right from problem definition to model evaluation and deployment…

Using session states to implement next/previous functionality

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This post is aimed toward demonstrating the use of session state in Streamlitfor storing info about certain variables and prevent them from updating across runs. But what is Streamlit ?

Streamlit is a python library which is aimed to make the process of building web applications to showcase your work very easy for python developers. Until the arrival of this package Flask and Djangowere the goto libraries which developers chose to use in order to develop and deploy their application over the web; however both these frameworks required the user to write HTML/CSS code to render their work as a…

Can Thomas Bayes tell the difference between Steve Rogers & Tony Stark?

This is the final post in a three part series which demonstrates the process of building a simple ML model and deploying it to an API endpoint. Previously, we have seen how to scrape data from the web for building a dataset of dialogues narrated by the two characters Captain America and Iron Man. Subsequently we saw an expository overview of the Naive Bayes Algorithm and built a model (dictionary of conditional probabilities) to identify the author given a dialogue. You can refer for getting an overview of the model building phase.

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As an ML practitioner, it is…

Can Thomas Bayes tell the difference between Steve Rogers & Tony Stark?

This post is the second in a series of three posts which aim to build a naive bayes classification algorithm in an end to end fashion. In the , we looked at curating the data for this problem: We scraped dialogues for both Captain America and Iron Man from the transcripts of Captain America: The First Avenger, Iron Man and Avengers: Endgame respectively. We then processed them to remove all action/scene description cues and only retain the spoken word by both our characters and created a dataframe out of the same and saved them as csv files.

Image from Pixabay Credits:

You can…

Can Thomas Bayes tell the difference between Steve Rogers & Tony Stark?

This post is the first in a three part series which aims to implement a Machine Learning Algorithm in an end to end manner using dockers. The underlying objective of this problem is to build a classifier using Naive Bayes Algorithm which could tell if a sentence is more likely to have been uttered by Steve Rogers aka Captain America or Tony Stark aka Iron Man. I will be using both the names of both characters to suit the context through the remainder of this post and subsequent ones.

Note: Some websites do not allow for scraping of data. Please…

Build your own blurring/background modification functionality in videos

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With the surge in use of video calling services during the COVID lockdown, many players are offering a service where the user of the service could blur the background or add a custom background etc. (Zoom, MS-Teams etc.) This is a classic use case of image segmentation where the object of interest is located and the pixels barring this region are modified/substituted.

There are many deep learning architectures which could be used to solve the instance segmentation problem and today we’re going to useDeeplab-v3 which is a State of the Art semantic image segmentation model which comes in many flavors…

Predicting the trajectory of stocks interactively using Deep Learning

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The table of contents of this post is as follows, click on any bullet to toggle to the respective section


Time series data has been around for quite a while and many people have studied them and came up with ways to analyze the data to find meaningful insights and subsequently use it to make reliable predictions as to how the series will progress in the future. Stock market…

How to CRUD with pymongo

This post aims to explain how can pymongo be used in order to interface with mongoDB to perform CRUD operations. In order to follow through this post, it’s recommended but not compulsory if you have a basic working knowledge of mongoDB and what it is. The topics covered in this post are as follows

If you’re interested only in a specific section, click on the topic above to…

Making the internet a safe space one word at a time

The internet has become a basic necessity in recent times and a lot of things which happen physically in our world are on the verge of being digitised. Already a substantial proportion of the world population uses the internet for day to day chores, entertainment, academic research etc. It then is a big responsibility to keep the internet a safe space for everyone to come and interact because there are all sorts of people posting stuff on the internet without being conscious of its consequences.

This post goes through the process of making a text classifier which takes in a…

Vinayak Nayak

AI Developer, Data Science Enthusiast

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