DataCamp Weekly: Python IDEs, AI Research, R packages, your data science career

Python IDEs, AI Research, improving R packages, and how to best start your data science career. [DataCamp]( DataCamp Weekly Issue #3 ― June 27, 2017 Hi everyone! A lot to talk about this week in the data science world! So let’s jump right in. This week we’re talking about Python IDEs, AI Research, improving R packages, and how to best start your data science career. Enjoy! Like what you’re seeing? Forward to a friend! Received this email from a friend? [Sign up]( for a DataCamp account to to receive a dose of data science every Tuesday. --------------------------------------------------------------- Projects & Resources [Top 5 Python IDEs for Data Science]( In this post, Paulo Vasconcellos explains what an IDE is and lays out a useful guide to help you choose your python IDE. Ever wonder what the differences between Spyder, Jupyter, PyCharm and Atom are? Find out here. [datacamp.com]( [How do I learn Python in depth?]( Once you learn the basics of Python, how do you move on to learn more complex concepts? DataCamp’s Karlijn Willems answers these questions and links to useful resources to deepen your knowledge in Python. Worth the read for those looking for additional resources for Python. [quora.com]( [Scikit-Learn Tutorial: Baseball Analytics in Python Pt 2]( This is part 2 of our baseball analytics in python project. Daniel Poston will guide you through testing out a regression model and a random forest model from the Scikit-Learn library to predict which player will be voted into the Hall of Fame, based on the player’s statistics and awards. [datacamp.com]( [Automatic tools for improving R packages]( Looking for tools to improve your R package? Mäelle Salmon details her favorite tools to improve R packages, some of which have flown under the radar and you might not know about! [masalmon.eu]( In The News [Introducing Dash: a Python alternative to Shiny for reactive visualizations]( Plotly just released Dash, a user interface library for creating analytical web applications. Similar to R’s Shiny, Dash makes it easy to build complex apps containing interactive elements. Promising tool for Python users. [medium.com]( [Measuring the Progress of AI Research]( What is the current status of AI research? Stay in the loop thanks to this really cool project that collects problems and datasets from AI research literature, and tracks progress on them. Great read to impress your friends. [eff.org]( [Developers Who Use Spaces Make More Money Than Those Who Use Tabs]( Should you use spaces or tabs when developing software? If you want to make more money it sounds like spaces is the way to go. DataCamp instructor and prominent blogger David Robinson dug into the data from the Stack Overflow 2017 Developer Survey. [stackoverflow.blog]( [9 Mistakes to Avoid When Starting Your Career in Data Science]( As a data scientist early in your career, your time, energy and motivation are your lifeblood. This post will help you avoid costly mistakes when learning data science, applying for a job, and during the interview process. Very useful. [elitedatascience.com]( [Face Recognition in R]( Cool project leveraging the power of Python from within R to create a simple face recognition program. It determines if a picture has a face in it, and saves it appropriately. [stoltzmaniac.com]( Elsewhere - [Top 50 ggplot2 Visualizations - The Master List (With Full R Code)]( - [Google launches its AI-powered jobs search engine]( - [Track changes in data with the lumberjack]( Jobs - [Data analyst – infectious disease mapping, John Drake (University of Georgia), Athens Georgia, USA]( - [Kenya Product Innovations Analyst, One Acre Fund, Kenya]( - [Junior Data Scientist, Apsara Capital, London]( - [Data Scientist - China Innovation Hub, McKinsey & Company, Beijing]( - [Data Scientist, Amazon, NYC]( --------------------------------------------------------------- See something interesting? Share via [Facebook]( [LinkedIn]( [Twitter](. That's all for now. Have a great week! DataCamp Inc. 2067 Massachusetts avenue Cambridge MA 02140 [Unsubscribe](