Newsletter Subject

Fake News Detection with Data Science

From

datacamp.com

Email Address

team@datacamp.com

Sent On

Tue, Mar 20, 2018 01:36 PM

Email Preheader Text

Alternatives to Excel. Analyze Cryptocurrency Portfolios. What should you post on your data science

Alternatives to Excel. Analyze Cryptocurrency Portfolios. What should you post on your data science blog. Text Sentiment Analysis. K-Means Clustering.  ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌  [DataCamp](  ISSUE #39 — MARCH 20, 2018  DataCamp Weekly Hi there - we're back to share what the DataCamp community has upvoted the most this past week. Including alternatives to Excel, new podcast episode, geofacet comparison, data science career advice, Jupyter notebook to analyze your crypto portfolio, & more! Enjoy! [Share An Article](  Community Top Posts  [1]( [Fake News Detection with Data Science (with Mike Tamir)](  PODCAST  | 17 Upvotes   | 0 Comments   | Posted by hugobowne  How can data science and deep learning be leveraged to detect fake news? Listen to Mike Tamir, Head of Data Science at Uber ATG, who is building out a data science product that classifies text as news, editorial, satire, hate speech and fake news, among others in this episode of the DataFramed podcast.  [2]( [Alternatives from R and Python for Certain Excel Tasks](  EXCEL  | 15 Upvotes   | 0 Comments   | Posted by gabrieldeselding  This post explains when it is adequate to use spreadsheets and when it is desirable to switch to more powerful technologies.  [3]( [Text Sentiment Analysis : 3 tidytext Lexicon Options](  DATA MANIPULATION  | 13 Upvotes   | 0 Comments   | Posted by terrychang  The blog post's objective is to share findings working with the R package, tidytext, plus highlight a succinct tidy text approach for text sentiment analysis. The goal is to find effective approaches to have more time for storytelling.  [4]( [My First Kaggle Contest and R Package](  KAGGLE  | 9 Upvotes   | 0 Comments   | Posted by karlijn  This blog post shares important discoveries and learnings from developing an R package for the first time, leadr, and completing a first Kaggle competition with some useful tips along the way.  [5]( [Introducing geofacet](  EDA  | 9 Upvotes   | 0 Comments   | Posted by rhafen  To geofacet is to take data representing geographic entities and apply a visualization method to each entity, with the resulting visualizations being laid out in a grid that mimics the original geography as closely as possible. This post introduces geofaceting and compares it to other methods.  [6]( [Your Analytics & Data Science New Year's Resolutions](  CAREER  | 7 Upvotes   | 0 Comments   | Posted by lindaburtch  Making career resolutions may seem like a nebulous concept, but in fast-evolving fields like data science and analytics, it's wise to take the time to evaluate your goals and where you'd like to progress! Here are some thoughts on resolutions for data scientists in 2018.  [7]( [Understanding 2D Dilated Convolution Operation with Examples in Numpy](  DEEP LEARNING  | 6 Upvotes   | 0 Comments   | Posted by jaedukseo  This post is an introduction to Dilated Convolution Operation implementation. Follow this step by step guide to get a full understanding of this concept.  [8]( [K-Means Clustering in R Tutorial](  MACHINE LEARNING  | 6 Upvotes   | 0 Comments   | Posted by cjsejal  Learn all about clustering and, more specifically, k-means in this R Tutorial, where you'll focus on a case study with Uber data.  [9]( [I Built A Jupyter Notebook That Will Analyze Cryptocurrency Portfolios](  CRYPTOCURRENCY  | 6 Upvotes   | 0 Comments   | Posted by theov  The amount of engagement in the crypto investment space needs no introduction. With market caps, volumes, and public awareness on the rise, the author made a simple Jupyter notebook to get a clearer and broader viewpoint into the investment activities within their own crypto portfolio.  [10]( [What Should You Post on Your Data Science Blog?](  LEARNING DATA SCIENCE  | 5 Upvotes   | 0 Comments   | Posted by gardnercw  Don't post baby steps. but don't wait for finished products either!   [DataCamp Community]( BY THE COMMUNITY, FOR THE COMMUNITY [Discover](  Categorical Spatial Interpolation with R   That's all for now. Have a great week!   [DataCamp] [DataCamp](  DataCamp Inc. | 350 Fifth Avenue | Suite 7730 | New York, NY 10118  [Facebook] [Facebook]( [Twitter] [Twitter]( [LinkedIn] [LinkedIn]( [YouTube] [YouTube](  [Unsubscribe]( Â

Marketing emails from datacamp.com

View More
Sent On

08/11/2024

Sent On

29/10/2024

Sent On

03/10/2024

Sent On

01/10/2024

Sent On

30/09/2024

Sent On

24/09/2024

Email Content Statistics

Subscribe Now

Subject Line Length

Data shows that subject lines with 6 to 10 words generated 21 percent higher open rate.

Subscribe Now

Average in this category

Subscribe Now

Number of Words

The more words in the content, the more time the user will need to spend reading. Get straight to the point with catchy short phrases and interesting photos and graphics.

Subscribe Now

Average in this category

Subscribe Now

Number of Images

More images or large images might cause the email to load slower. Aim for a balance of words and images.

Subscribe Now

Average in this category

Subscribe Now

Time to Read

Longer reading time requires more attention and patience from users. Aim for short phrases and catchy keywords.

Subscribe Now

Average in this category

Subscribe Now

Predicted open rate

Subscribe Now

Spam Score

Spam score is determined by a large number of checks performed on the content of the email. For the best delivery results, it is advised to lower your spam score as much as possible.

Subscribe Now

Flesch reading score

Flesch reading score measures how complex a text is. The lower the score, the more difficult the text is to read. The Flesch readability score uses the average length of your sentences (measured by the number of words) and the average number of syllables per word in an equation to calculate the reading ease. Text with a very high Flesch reading ease score (about 100) is straightforward and easy to read, with short sentences and no words of more than two syllables. Usually, a reading ease score of 60-70 is considered acceptable/normal for web copy.

Subscribe Now

Technologies

What powers this email? Every email we receive is parsed to determine the sending ESP and any additional email technologies used.

Subscribe Now

Email Size (not include images)

Font Used

No. Font Name
Subscribe Now

Copyright © 2019–2025 SimilarMail.