Self-paced courses are just sleeping pills; Industry experts are the right choice

Photo by Julia M Cameron from Pexels

I started my data science journey back in 2016. At that time, machine learning boot camps were much popular. The only requirement of the course was basic Python knowledge. I felt so happy because I used to play with Python codes at that time, so I opted for the course.

The usual practice of human beings — when we’re learning something new — is to try and collect as much material from different places. We may think that these resources will help us learn more. And, the more variety of materials you have, the more choice you can have to…

“No-Code” machine learning is the future

Photo by Ketut Subiyanto from Pexels

Python programming got the hype and the attention because of the popularity of data science. As of now, in 2021, we have two famous programming languages Python and R, for data science and analytics. But, if we talked about back in 2016, we were having a single famous programming language for data science modeling, Python.

Indeed, Python is also used for web development, and its Django & Flask framework is so much used in many industries. But, we have many other programming languages like Java, Javascript with its popular library React that can do that same web development efficiently. …

Handy features to improve your Python programming skills

Photo by vjapratama from Pexels

1. Condition Inside the print Function

Have you ever thought you could write the entire condition inside the function and print the output based on the conditions? Here is how you can achieve this:

print("odd" if int(input("Enter a num: "))%2 else "even")


The data science workflow is getting automated day by day

Photo by Andrea Piacquadio from Pexels

I have been in the data science field for the last half-decade when python programming came into the trend. Back then, in 2016, neural networks and deep learning were just some buzzy words. At that time, there was a hype about Google self-driving cars and reinforcement learning. But, most of the data science enthusiasts were not even aware of the working of neural networks.

Today in 2021, most companies are adopting a data science strategy to make more revenue by automating different scenarios and replacing dozens of IT people with a single data scientist who can automate the task of…

These are the unexplored gems of data science

Photo by Headshatter from Pexels

In the 21st-century data science has attracted a lot of attention and has been recognised as one of the most exciting fields to work on.

With the immense growth of data science and its applications, a number of Libraries, frameworks and toolkits have also been developed which along with the traditional data science libraries like Numpy, Pandas Matplotlib, Scikit-learn can make programmers’ lives easier.

In today’s article, we are going to take a look at 7 such libraries which are not widely used but can definitely help you improve your workflow.

1. Pandas_ml

Pandas_ml is a Python library that is made with…

OpenCV is not the only one

Photo by Mike from Pexels

Image processing is the phenomenon of manipulating an image to extract features from it.

In today’s world of computer vision and deep learning, different algorithms for image processing are heavily used to carry out edge detection, recognition, classification from a dataset of images.

Sometimes these algorithms are also applied to videos frame by frame to extract features from them.

In today’s article, we will take a look at the 5 best Python libraries that might help you to carry out manipulation of images like cropping, grayscaling etc.

1. OpenCV

OpenCV is one of the most popular and widely used libraries for image…

These small improvements can be crucial

Photo by Monstera from Pexels

Python is a fairly popular language among beginners as it is very easy to use. But behind the easy to understand syntax and shorter codes there are some minute details that everyone must take care of. Because ignoring these details may cause the breaking of your code and can be a reason for your headache.

This article will talk about 6 mistakes every beginner should avoid while coding in Python.

1. Version of Python:

This should be one of the main concerns for python programmers as a large number of Python versions are used by programmers across the globe. Two main versions that are…

These Libraries Will Amaze You

Source: Pexels

Python is now one of the most popular and fastest-growing programming languages. Its utility has been demonstrated in the fields of artificial intelligence and business analytics. Building cybersecurity solutions is yet another important application of technology.

Python has some amazing libraries that can be utilised in cybersecurity. The good thing is that most of these libraries are currently being utilised in the cybersecurity area. They are using python because it is much simple to learn and user-friendly.

In his article, I will share some useful libraries for creating cybersecurity solutions using python.

1. Nmap

Nmap is an open-source tool analyser that is…

Simple but effective tips for every python lovers

Photo by Miesha Maiden from Pexels

The compactness of Python can make a developer’s life a lot easier when writing lines and lines of code. But there are some lesser-known Python tricks that can surprise you with their amazing capabilities.

In today’s article, I will discuss 10 Python tips and tricks that will be really helpful for beginners to write more compact code. Knowing these tips and tricks will definitely save you some valuable time.

1. Walrus operator

The or operator is one of the latest additions to python 3.8. …

Missingno, Bokeh, Altair, Geoplotlib, and much more

Photo by Mike from Pexels

An important aspect of data science is visualising the data. When we have a fairly large set of data that we cannot comprehend only by going through it, we need to plot them in different formats to understand better. Visualisation packages make this job a lot easier for data scientists.

This article will talk about seven Python visualisation packages that you must try to plot your data. We have excluded Matplotlib from the list as it is fairly common and used by all data science enthusiasts.

1. Bokeh

Bokeh is a native Python library that is based on The Grammar of Graphics…

Pranjal Saxena

Data Scientist | 3x Top Writer | Connect me here for any data science advice:

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