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10 Most Popular Guest Authors on Analytics Vidhya in 2021
Our guest authors of 2021 AKA data science enthusiasts wrote numerous articles on our platform and added value to our community.
Sakshi Raheja 23 Dec, 2021
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Pre-trained Stacked Model to Detect Pneumonia
In this article, we will learn to design a model using pre-trained stacked which takes X-Ray pictures and detect if the person has Pneumonia.
Gunjan Agarwal 10 Dec, 2021
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Implementing Computer Vision – Face Detection
In this first article, we will focus on the introduction of computer vision, and the face detection application based on the Python OpenCV
Andre 09 Dec, 2021
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Top 10 Articles Published in 2021 on Analytics Vidhya
We organize a ‘Blogathon’ where the writers submit their entries. Let's take a look at the top 10 articles of data science in 2021.
Sakshi Raheja 23 Dec, 2021
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Stress Detection using AutoML: FEDOT Framework
In this article, we will learn how stress detection can take place using AutoML. We will use the FEDOT framework.
N_Lakshmi 08 Dec, 2021
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What Does numpy.random.seed() Do?
Explore the functionality of numpy.random.seed(), its syntax, code snippets, & applications in generating random numbers. Read Now!
Mohamed Thoufeeq 04 Apr, 2025
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Stock Price Prediction using LSTM and its Implementation
Discover LSTM for stock price prediction: understand its architecture, tackle challenges, implement in Python, and visualize results!
Siddharth M 01 May, 2025
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Bank Note Authentication using Keras Sequential Model
Keras is an open-source library that is used to implement ANN in Keras. We will use Keras Sequential Model to authenticate banknotes.
Prateek Majumder 03 Dec, 2021
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Using Django Framework For Making Exciting Data Science Projects – An Example Use Case
Django Framework is used for creating some really exciting data science projects. It is used to code the backend of a webpage in Python
Aryan Garg 03 Dec, 2021
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Cryptocurrency Price Prediction using ARIMA Model
ARIMA Model (AutoRegressive Integrated Moving Average)has 3 parameters p, d, and q accounting for seasonality, trend, and noise in the dataset
Sion 23 Oct, 2024
