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Data Science

A collection of 9 posts

FloydHub Cloud Setup Challenge:  Jupyter + TensorFlow in 44 seconds [WR]
Data Science

FloydHub Cloud Setup Challenge: Jupyter + TensorFlow in 44 seconds [WR]

Is it possible for data science beginners to get up and running in under 90 seconds? FloydHub’s team takes on the setup cloud challenge - and walks away with the trophy. (For now!)

  • Alessio Gozzoli
    Alessio Gozzoli
7 min read
Naïve Bayes for Machine Learning – From Zero to Hero
Data Science

Naïve Bayes for Machine Learning – From Zero to Hero

Bayes’ Theorem is about more than just conditional probability, and Naive Bayes is a flavor of the theorem which adds to its complexity and usefulness.

  • Anand Venkataraman
    Anand Venkataraman
16 min read
A Pirate's Guide to Accuracy, Precision, Recall, and Other Scores
Data Science

A Pirate's Guide to Accuracy, Precision, Recall, and Other Scores

Once you've built your classifier, you need to evaluate its effectiveness with metrics like accuracy, precision, recall, F1-Score, and ROC curve.

  • Philip Kiely
    Philip Kiely
15 min read
Multiprocessing vs. Threading in Python: What Every Data Scientist Needs to Know
Data Science

Multiprocessing vs. Threading in Python: What Every Data Scientist Needs to Know

This deep dive on Python parallelization libraries - multiprocessing and threading - will explain which to use when for different data scientist problem sets.

  • Sumit Ghosh
    Sumit Ghosh
14 min read
When Not to Choose the Best NLP Model
Deep Learning

When Not to Choose the Best NLP Model

The world of NLP already contains an assortment of pre-trained models and techniques. This article discusses how to best discern which model will work for your goals.

  • Cathal Horan
    Cathal Horan
15 min read
N-Shot Learning: Learning More with Less Data
Deep Learning

N-Shot Learning: Learning More with Less Data

Is it possible to use machine learning with small data? Yes, it is! Here's N-Shot Learning.

  • Heet Sankesara
    Heet Sankesara
15 min read
Becoming One With the Data
Deep Learning

Becoming One With the Data

This article discusses effective ways of handling the data in machine learning projects.

  • Sayak Paul
    Sayak Paul
29 min read
DIY Data: Web Scraping with Python and BeautifulSoup
Data Science

DIY Data: Web Scraping with Python and BeautifulSoup

Getting sufficient clean, reliable data is one of the hardest parts of data science. Web scraping automates the process of visiting web pages, downloading the data, and cleaning the results. With this technique, we can create new datasets from a large compendium of web pages.

  • Philip Kiely
    Philip Kiely
14 min read
Statistics for Data Science
Data Science

Statistics for Data Science

The article elucidates the importance of statistics in the field of data science, wherein "Statistics" is imagined as a friend to a data scientist and their friendship is unraveled.

  • Anand Venkataraman
    Anand Venkataraman
21 min read
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