Refer to this blog for data visualization, data cleaning, model building, model dumping, and also how to render your results with Flask on a web page..

Image for post
Image for post
Screenshot from my Jupytr Notebook!

So called “ Machine Learning Enthusiasts ” these days get an ear to ear grin whenever they train a model and get a good accuracy on their business problem. But have you ever wondered about end customer of the model ? Will he be able to understand your accuracy results ? Forget accuracy, can he even use your model on his own ?

I believe every ML enthusiast should be aware of how to “Productionize your model” as this is one of the most important step in your ML project lifecycle. Without model deployment, you cannot communicate your model output to general public. Your model would just be sitting in your Jupytr Notebook (or any other tool you might be using). …


Refer this blog if you are a NumPy beginner or someone who’s looking back to revising NumPy. Post also includes some advance NumPy topics like vectorization, broadcasting, NumPy Methods cheat sheet etc !

Image for post
Image for post
Photo by Markus Spiske on Unsplash

What’s Numpy ?

For starters, Numpy is short for Numerical Python. According to “numpy.org”,

NumPy is the fundamental package for scientific computing in Python.

Scientific computing here refers to tons of things Numpy can do on arrays including mathematical, logical, shape manipulation, sorting, selecting, I/O, discrete Fourier transforms, basic linear algebra, basic statistical operations, random simulation and much more.

In short, it gives programmer means to interpret block of homogenous data. …


Python untold

Image for post
Image for post
Photo by Clément H on Unsplash

According to IEEE Computer Society, for year 2020 Python continues to be the best programming language which a developer should know. Whether it’s web development, GUI desktop app or a ML-pipeline, python turns out to be common stop shop.

I won’t dare myself to jump into python vs other languages debate but we can all agree that python is quite general purpose and widely acceptable. All together, learning Python is a good trade which can definitely pay-off well.

When I started my Python learning journey (which still continues..), I got comfortable with it within a week or so and all thanks to literal English syntax and tons of awesome libraries with innumerable documentation sources out there. My confidence with Python started to build up but soon out of nowhere I came across couple of topics which surprisingly I had never heard of. …


Image for post
Image for post
Photo by Benjamin Voros on Unsplash

As I was thinking about appropriate topic for my first Medium post, there came an opportunity from a company (name cannot be disclosed) with a business problem. We were mailed a dataset and on a zoom call we were given instructions to solve the problem. This blog post discusses Twitter sentiment analysis that I performed on the humongous dataset (More than 2.8 Million tweets) and my 2 day journey which discusses about my experience. So let’s begin !!

About Dataset

It was a typical twitter mined dataset with no label values which makes our problem unsupervised. …

About

Puneet Gajwal

A Data Science Enthusiast who believes world is about to get transformed by A.I, we better keep up ! Initiate contact on puneet.gajwal99@gmail.com !

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store