Introduction
Our long-time followers know how much writing is at the core of this organization. After all, writing data science articles is from where it all started. And with each passing year, we have achieved nothing short of miracles with this intention to teach people with our words.
At the end of 2021, we are proud to say that the Analytics Vidhya community has scaled to new heights. With more than 1000 quality articles published, this year has simply been exciting, with Blogathon serving as an anchor bringing these amazing articles from our ever-learning community.
In this article, we are going to mention the top articles published on our platform.
Note- The articles have been chosen on the basis of the number of views from the beginning of 2021 to 30 Nov 2021.
Rank One: Top 30 MCQs to Ace Your Data Science Interviews
With ‘Artificial Intelligence’ and ‘Machine Learning’ getting popular every day. Data science as an industry is booming more than ever, in the post COVID era. The 30 MCQs are from the three most relevant fields:
- Probability, Statistics and Machine Learning Algorithms
- Deep Learning
- Coding Questions
These questions will help you to check your knowledge or if you’re preparing for an interview. So, What are you waiting for? Let’s get here.
Rank Two: Python Tutorial: Working with CSV file for Data Science
CSV stands for ‘Comma Separated Values’. Storing data in tabular form as plain text is the simplest form. CSV files can be handled in different ways in Python.
This article will help you learn those different ways to read files. This will help you to expand, learn about various observations and records and how you could read them quickly amidst your project timelines. This will act as a glorious feature in your Data Science Journey.
Click here to read more.
Rank Three: Interesting Python Projects With Code for Beginners!
Some of the data scientists often feel bored when they start programming. For them, we bring three of the coolest python projects. These can be implemented at their workplace or internships. These are:
- QR Code Generation
- GUI Application for calendar
- Convert Image to a Pencil Sketch
This article will give you details about how you can learn these projects and generate codes. Also, at the end of this article, the author has suggested some more python projects which you could try out.
Want to know more? Click here.
Rank Four: Logistic Regression- Supervised Learning Algorithm for Classification
The method to classify the data is known as Logistic Regression which comes under the branch of Machine Learning. We can classify the data into binary and multi-class logistic regression.
This article will give you all an overview of the logistic algorithms for beginners. It will tell you how it is different from linear regression? Why do we have a curved line for logistic regression and not a straight line? Also, some applications of logistic regression. Want to know more? Click here.
Rank Five: Making Programming with Date and Time, less painless
Date and Time are the two most crucial aspects of each one of our lives. In the data science industry, they’re considered one of the most challenging tasks. With different countries and their time zones, days get mixed up, and sometimes it is hard for us to keep a track of it. For this, we have the built-in Python module DateTime, that comes to our rescue.
Interesting, isn’t it? This article will clarify a lot of things like why programming with dates and times is hard, how computers measure time, the DateTime module in Python, creating DateTime objects, and so on.
So, are you up for a challenge and deal with different time zones? Click here to read more.
Rank Six: Support Vector Machine
To learn about Support Vector Machine (SVM), you should have some prior knowledge about Linear Regression, Logistic Regression and its implementation. You could read about these topics on our blog.
SVM is a supervised learning algorithm that is used for both classification and regression analysis. However, data scientists like to use this primarily for classification purposes. This article entails various details like decision rules in SVM, determining the hyperplane in N-dimensions, and other topics in detail.
Click here to read more.
Rank Seven: Is the Tableau Era Coming to an End?
In 2003, Tableau was introduced to the users, who heralded the tool as ‘revolutionary’ and ‘life-changing’. But now, the times are changing. To know more details about Tableau and its product, read here.
To move into a new golden age of data, we need to address and remedy some of the ghosts of the Tableau era that are holding us back. Read here to know more about Tableau’s future, how companies are feeling the Data FOMO, fear of missing out.
Rank Eight: Seismic Analysis with Python
Earthquakes are one of the major natural disasters which have killed more than 750,000 people worldwide. This article discusses and shows two datasets from Kaggle:
– Significant Earthquakes, 1965-2916
– Tectonic Plate Boundaries
Most of the origins of these Earthquakes can be traced back to geological causes, the dynamics of tectonic plates. As the distance from plate boundaries magnifies, in contrast, the depth of earthquake decreases in shallowness.
Let’s get started, read here and then, try out these analyses by yourself.
Rank Nine: Introduction to Convolutional Neural Networks (CNN)
In today’s era, where technology is moving at a lightning speed, deep learning has proved to be a very powerful tool because of its ability to handle large amounts of data. It helps to hide different layers in pattern recognition which is unique to the traditional techniques.
Convolutional Neural Networks are the most popular deep neural networks. In this article, you will get to know more about what exactly is CNN, how does it work, the pooling layer, the limitations of CNN and so on.
What do you think? Has CNN caused a revolution in artificial intelligence?
Want to know more? Read here.
Rank Ten: Introduction to Python Programming (Beginner’s Guide)
This article is for everyone who isn’t from a data science background but is passionate to learn about it. To know the basics of Python, read here.
Python is a general-purpose programming language as it is used in almost every domain we can think of as mentioned below:
- Web Development
- Software Development
- Game Development
- AI & ML
- Data Analytics
There are so many of your queries that haven’t been answered till now. Are you still wondering why python is in-demand? This article is your go-to guide to know about the basics, applications of python, how to become a better programmer and so on. Read here to know.
That’s all from our end folks! Hope you enjoyed reading these articles. Comment below and share with us your views and what you would like to read in 2022.
I am a passionate writer and avid reader who finds joy in weaving stories through the lens of data analytics and visualization. With a knack for blending creativity with numbers, I transform complex datasets into compelling narratives. Whether it's writing insightful blogs or crafting visual stories from data, I navigate both worlds with ease and enthusiasm.
A lover of both chai and coffee, I believe the right brew sparks creativity and sharpens focus—fueling my journey in the ever-evolving field of analytics. For me, every dataset holds a story, and I am always on a quest to uncover it.
