Emerging Ecosystem: Data Science and Machine Learning Software, Analyzed

[unable to retrieve full-text content]We examine which top tools are “friends”, their Python vs R bias, and which work well with Spark/Hadoop and Deep Learning, and identify an emerging Big Data Deep Learning ecosystem.
Original Post: Emerging Ecosystem: Data Science and Machine Learning Software, Analyzed

R leads, Python gains in 2017 Burtch Works Survey

For the past four years, recruiting firm Burtch Works has conducted a simple survey of data scientists with just one question: “Which do you prefer to use — SAS, R or Python”. The results for this year’s survey of 1,046 respondents are in: R: 40% (2016: 42%) SAS: 34% (2016: 39%) Python: 26% (2016: 20%) Compared to last year’s results, Python has gained 6 percentage points, mainly at the expense of SAS. (2016 results do not add to 100% due to rounding.) The trend for the commercial tool compared to the open-source tools is apparent looking at the data from all four years: (Note: Python has only been an option for respondents in the last two surveys.) Demographic breakdowns, included in the survey analysis linked below, show that SAS remains popular with more years of experience (more than 16 years),…
Original Post: R leads, Python gains in 2017 Burtch Works Survey

Best Data Science Courses from Udemy (only $10 till June 21)

[unable to retrieve full-text content]Here are some of the best courses in data science from Udemy, covering Data Science, Machine Learning, Python, Spark, Tableau, and Hadoop – only $10 until June 21, 2017.
Original Post: Best Data Science Courses from Udemy (only till June 21)

KDnuggets™ News 17:n23, Jun 14: The Practice of Machine Learning, Data Science Implementation, and Feature Selection

[unable to retrieve full-text content]A Practical Guide to Machine Learning; Your Checklist to Get Data Science Implemented in Production; The Practical Importance of Feature Selection; Machine Learning in Real Life: Tales from the Trenches.
Original Post: KDnuggets™ News 17:n23, Jun 14: The Practice of Machine Learning, Data Science Implementation, and Feature Selection

Top 15 Python Libraries for Data Science in 2017

[unable to retrieve full-text content]Since all of the libraries are open sourced, we have added commits, contributors count and other metrics from Github, which could be served as a proxy metrics for library popularity.
Original Post: Top 15 Python Libraries for Data Science in 2017

How Feature Engineering Can Help You Do Well in a Kaggle Competition – Part I

[unable to retrieve full-text content]As I scroll through the leaderboard page, I found my name in the 19th position, which was the top 2% from nearly 1,000 competitors. Not bad for the first Kaggle competition I had decided to put a real effort in!
Original Post: How Feature Engineering Can Help You Do Well in a Kaggle Competition – Part I

KDnuggets™ News 17:n22, Jun 7: 7 Steps to Mastering Data Preparation with Python; Why Does Deep Learning Not Have a Local Minimum?

[unable to retrieve full-text content]7 Steps to Mastering Data Preparation with Python; Why Does Deep Learning Not Have a Local Minimum?; 7 Techniques to Handle Imbalanced Data; Which Machine Learning Algorithm Should I Use?; Is Regression Analysis Really Machine Learning?
Original Post: KDnuggets™ News 17:n22, Jun 7: 7 Steps to Mastering Data Preparation with Python; Why Does Deep Learning Not Have a Local Minimum?

KDnuggets™ News 17:n22, Jun 7: 7 Steps to Mastering Data Preparation with Python; Why Does Deep Learning Not Have a Local Minimum?

[unable to retrieve full-text content]7 Steps to Mastering Data Preparation with Python; Why Does Deep Learning Not Have a Local Minimum?; 7 Techniques to Handle Imbalanced Data; Which Machine Learning Algorithm Should I Use?; Is Regression Analysis Really Machine Learning?
Original Post: KDnuggets™ News 17:n22, Jun 7: 7 Steps to Mastering Data Preparation with Python; Why Does Deep Learning Not Have a Local Minimum?

6 Interesting Things You Can Do with Python on Facebook Data

[unable to retrieve full-text content]Facebook has a huge amount of data that is available for you to explore, you can do many things with this data. I will be sharing my experience with you on how you can use the Facebook Graph API for analysis with Python.
Original Post: 6 Interesting Things You Can Do with Python on Facebook Data

7 Steps to Mastering Data Preparation with Python

[unable to retrieve full-text content]Follow these 7 steps for mastering data preparation, covering the concepts, the individual tasks, as well as different approaches to tackling the entire process from within the Python ecosystem.
Original Post: 7 Steps to Mastering Data Preparation with Python