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Frequentist vs Bayesian Statistics in Data Science
Frequentist vs Bayesian: Definition, tests, methods, applications, examples, which one to use, which one is better frequentist or Bayesian? Click to explore
Analytics Vidhya 17 Apr, 2024
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Using AWS Data Wrangler with AWS Glue Job 2.0
Lets walk through a hypothetical use-case to read data from the AWS glue catalog table and obtain filter value to retrieve data from redshift
Guest Blog 08 Mar, 2021
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Generate Background Blur using Deep Learning in Python with this Simple Tutorial
The background blur effect which is also known as “bokeh” is a well-known effect that is used by many of us mainly for close up shots.
Guest Blog 20 Oct, 2020
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Top Female AI Influencers in 2020 Who Rocked the Data Science World!
We list down Top Female AI influencers of 2020 who set a high bar in the community with their work and have become a beacon of inspiration.
Shipra Saxena 16 Dec, 2020
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Add rows to Pandas Dataframe
Unlock the power of data manipulation with our comprehensive guide on appending row in Pandas dataframe. Learn essential techniques today!
Pankaj Singh 29 May, 2025
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Sentiment Analysis with LSTM and TorchText with Code and Explanation
In this article, we will see every single details that you need to know for sentiment analysis using the LSTM and torchtext library
Pritesh 14 Oct, 2021
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The Origin of Big Data Analytics
Big data analytics helps businesses and organizations make better decisions by uncovering information that would otherwise be hidden.
Trupti Dekate 12 Oct, 2022
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Exploratory Data Analysis of Zomato Bangalore Restaurants
In this article, we performed exploratory data analysis on the Zomato Bangalore Restaurants dataset based on various ratings.
Yamini 12 Oct, 2024
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Real-Time Object Detection with SSDs: Single Shot MultiBox Detectors
Explore the power of SSDs (Single Shot MultiBox Detectors) for real-time object detection in this comprehensive article.
Neha Vishwakarma 17 Nov, 2023
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Textual Statistical Analysis Using pyNLPL (Pineapple) Library
Learn how to perform text analysis using the pyNLPL library, including term co-occurrence, frequency lists, and document similarity.
Adil Mohammed 12 May, 2025
