This article was written by
Watching the appeal and applications of machine intelligence expand:
Almost a year ago, we published our now-annual …Continue
Added by Emmanuelle Rieuf on November 9, 2016 at 5:30pm — No Comments
We are living in the era of technological transformation that is bringing about changes in the way we take decisions. As big data is becoming pervasive across all the industries, use of machines to find patterns and predict future is gaining a lot of prominence in the…Continue
Added by Ashish Sukhadeve on November 9, 2016 at 10:30am — No Comments
The Python Data Science Handbook provides a reference to the breadth of computational and statistical methods that are central to data-intensive science, research, and discovery. People with a programming background who want to use Python effectively for data science tasks will learn how to face a variety of problems: e.g., how can I read this data format into my…Continue
Added by Emmanuelle Rieuf on November 9, 2016 at 8:30am — No Comments
In this post, I show a network analysis of the R and Python ecosystems in terms of their competitors. The objective of the post is to -
To identify the typical substitutes/ competitors of a tool, I use the Google search autofill recommendations.…Continue
Added by Archisman Majumdar on November 9, 2016 at 1:30am — No Comments
Psst! Want to know a secret?
Engineers are no longer taking home a five figure salary. Instead, they are now expanding their reach to earn six figure incomes.
Wondering how they do it?
Well, for starters, they are well read and know what's trending in the industry. If there is a hiring pattern in the industry, they realize the potential of getting in it and exploring it further.
But, how can you replicate the same for your career?
Data Science can't be…Continue
This article on a complete tutorial on data exploration, was posted by Sunil Ray. Sunil is a Business Analytics and Intelligence professional with deep experience in the Indian Insurance industry.
There are no shortcuts for data exploration. If you are in a state of mind, that machine learning can sail you away from every data storm, trust me, it won’t. After some point of time, you’ll realize that you are struggling at improving model’s…Continue
Added by Emmanuelle Rieuf on November 8, 2016 at 9:00am — No Comments
Do you want to learn the history of data visualization? Or do you want to learn how to create more engaging visualizations and see some examples? It’s easy to feel overwhelmed with the amount of information available today, which is why sometimes the answer can be as simple as picking up a good book.
Summary: Next time you bring up Artificial Intelligence and your non-data scientist friends all say “Watson” here’s some perspective you can offer. Their understanding of AI and Watson is very likely to be inaccurate. Here’s what you need to know to set them straight.
When conversation with my non-data scientist friends turns to AI it’s almost inevitable that at least one will remark on the wonders of Watson. To many of the uninformed, Watson is…Continue
Added by William Vorhies on November 8, 2016 at 7:30am — No Comments
This article was posted by Saurav Kaushik. Saurav is a Data Science enthusiast, currently in the final year of his graduation at MAIT, New Delhi. He loves to use machine learning and analytics to solve complex data problems.
Have you come across a situation when a Chief Marketing Officer of a company tells you – “Help me understand our customers better so that we can market our products to them in a better manner!”
I did and the analyst in…Continue
Added by Emmanuelle Rieuf on November 7, 2016 at 7:00pm — No Comments
This article was written by Sebastian Ruder. Sebastian is a PhD student in Natural Language Processing and a research scientist at AYLIEN. He blogs about Machine Learning, Deep Learning, NLP, and startups.
Gradient descent is one of the most popular algorithms to perform optimization and by far the most common way to optimize neural networks. At the same time, every state-of-the-art Deep Learning library contains implementations of various algorithms to optimize gradient…Continue
Added by Emmanuelle Rieuf on November 7, 2016 at 6:30pm — No Comments
The shortage of data scientists is a hindrance to the widespread adoption of analytics across many industries.
At the same time, the preponderance of multiple tools, techniques and knowledge base along with the rapidly changing data science landscape make it difficult for analytics leaders to hire the right talent for their data science team. The attrition rate in this industry is also high due to which employers end up spending a lot of time and money to hire a data…Continue
Added by Aatash Shah on November 7, 2016 at 4:30am — No Comments
This article was written by Ryan Grim. Ryan is the Washington bureau chief for The Huffington Post and an MSNBC contributor. He is a former staff reporter with Politico.com and Washington City Paper, as well as the author of the book "This Is Your Country on Drugs". Nate Silver is a famous statistician, founder and editor in chief of FiveThirtyEight. Some of the arguments in this article are about the type of regression being used.…Continue
This blog contains some snippets of code that I tend to use in Java. I acknowledge that somebody else writing this blog might include different code. Except for a short course at Sun Educational Services, most of my Java programming skills are self-taught. I’m unsure if people with formal backgrounds in computer science might have different styles and conventions. Mine have been shaped primarily by my needs.
Creating a Graphical User Interface…Continue
Added by Don Philip Faithful on November 6, 2016 at 8:00am — No Comments
Data science is first and foremost a talent-based discipline and capability. Platforms, tools and IT infrastructure play an important but secondary role. Nevertheless, software and technology companies around the globe spend significant amounts of money talking busin…Continue
Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week.
Featured Resources and Technical ContributionsContinue
Added by Vincent Granville on November 5, 2016 at 1:30pm — No Comments
This article was written by Stephanie Kim. Stephanie has a professional experience with data mining and processing including natural language processing along with a small amount of machine learning and script automation.
Who swears more? Do Twitter users who mention Donald Trump swear more than those who mention Hillary Clinton? Let’s find out by…Continue
Added by Emmanuelle Rieuf on November 4, 2016 at 12:00pm — No Comments
There’s a lot of buzzword around the term “Sentiment Analysis” and the various ways of doing it. Great! So you report with reasonable accuracies what the sentiment about a particular brand or product is.
After publishing this report, your client comes back to you and…Continue
Added by Vivek Kalyanarangan on November 4, 2016 at 5:00am — No Comments
“It is a capital mistake to theorise before one has data.”
― Arthur Conan Doyle, The Adventures of Sherlock Holmes…Continue
Added by Jari Turkia on November 3, 2016 at 1:30am — No Comments
Many people worry that "AI" will usher in a new Industrial revolution where machines replace humans. My take is that it will be more like the Printing press revolution that launched the Age of Enlightenment! The effect will be less of soaring productivity but more of better decision-making leading to a SMARTER society.
Part of the problem is the misnomer, "AI or artificial intelligence"…Continue
Added by PG Madhavan on November 2, 2016 at 12:00pm — No Comments
Guest blog by Brando Rohrer. Brandon is an author and deep learning developer. He has worked as Principal Data Scientist at Microsoft, as well as for DuPont Pioneer and Sandia National Laboratories. Brandon earned a Ph.D. in Mechanical Engineering from the Massachusetts Institute of Technology.…Continue