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 Data Science Books You Should Start Reading in 2021
Check out this curated list of the best data science books for any level.
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The Three Edge Case Culprits: Bias, Variance, and Unpredictability
Edge cases occur for three basic reasons: Bias – the ML system is too ‘simple’; Variance – the ML system is too ‘inexperienced’; Unpredictability – the ML system operates in an environment full of surprises. How do we recognize these edge cases situations, and what can we do about them?
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Production-Ready Machine Learning NLP API with FastAPI and spaCy
Learn how to implement an API based on FastAPI and spaCy for Named Entity Recognition (NER), and see why the author used FastAPI to quickly build a fast and robust machine learning API.
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Time Series Forecasting with PyCaret Regression Module
PyCaret is an alternate low-code library that can be used to replace hundreds of lines of code with few lines only. See how to use PyCaret's Regression Module for Time Series Forecasting.
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Data Analysis Using Tableau
Read this overview of using Tableau for sale data analysis, and see how visualization can help tell the business story.
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Want To Get Good At Time Series Forecasting? Predict The Weather
This article is designed to help the reader understand the components of a time series.
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Build an Effective Data Analytics Team and Project Ecosystem for Success
Apply these techniques to create a data analytics program that delivers solutions that delight end-users and meet their needs.
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6 Mistakes To Avoid While Training Your Machine Learning Model
While training the AI model, multi-stage activities are performed to utilize the training data in the best manner, so that outcomes are satisfying. So, here are the 6 common mistakes you need to understand to make sure your AI model is successful.
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Top 3 Statistical Paradoxes in Data Science
Observation bias and sub-group differences generate statistical paradoxes.
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ETL in the Cloud: Transforming Big Data Analytics with Data Warehouse Automation
Today, organizations are increasingly implementing cloud ETL tools to handle large data sets. With data sets becoming larger by the day, unified ETL tools have become crucial for data integration needs of enterprises.
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Data Science Books You Should Start Reading in 2021
Top 3 Statistical Paradoxes in Data Science