Feb
2016 Mar Opinions, Interviews, Reports
All (114) | Courses, Education (9) | Meetings (11) | News, Features (18) | Opinions, Interviews, Reports (38) | Publications (2) | Software (9) | Top Tweets (4) | Tutorials, Overviews (18) | Webcasts (5)
- Pattern Curators of the Cognitive Era
- Mar 31, 2016.
Machine learning has a critical dependency on human learning. But not just on Data Scientists, but on legions of people who legions of individuals who prepare training data to guide algorithms.
- The Rise of Dark Data and How It Can Be Harnessed
- Mar 31, 2016.
Dark data isn’t just a small portion of big data, but the biggest and fastest growing. It holds massive potential for those who can harness it successfully.
- Don’t be afraid to Fail – Start Now with Data Science
- Mar 30, 2016.
An argument for why aspiring data scientists should stop waiting for permission and start doing data science.
- HR Analytics Starter Kit – Intro to R
- Mar 28, 2016.
We review tools to help you start performing HR analytics with a focus on R platform, and providing useful examples for the HR and Workforce analytics using R.
- Don’t Buy Machine Learning
- Mar 28, 2016.
In many projects, the amount of effort spent on R&D on Machine Learning is usually a small fraction of the total effort, or it’s not even there because we plan it for a future phase after building the application first.
- How to combat financial fraud by using big data?
- Mar 25, 2016.
Financial fraud methods are becoming more sophisticated and the techniques to combat such attacks also need to evolve. Big data has brought with it novel fraud detection and prevention techniques such as behavioral analysis and real-time detection to give fraud fighting techniques a new perspective.
- Whether Evolution or Revolution, The Internet of Things is Here to Stay
- Mar 25, 2016.
The Internet of Things (IoT) is the next boom you need to know about, and insurance provider AIG has recently released a no-nonsense whitepaper providing an overview of the landscape in the space.
- Data Science Tools – Are Proprietary Vendors Still Relevant?
- Mar 25, 2016.
We examine and quantify the dramatic impact of open source tools like R and Python on SAS, IBM, Microsoft, and other proprietary Data Science vendors. We also investigate how open source tools were faring against each other, which are growing, which are falling, and look R versus Python debate.
- Ethics In Machine Learning: What we learned from Tay chatbot fiasco?
- Mar 25, 2016.
As Microsoft chatbot Tay showed, Machine Learning brings us into a new world where our views on ethics and political correctness will be challenged. ML learns from us. In both good and bad ways, it reflects what we really are.
- “Citizen Data Scientist” Revolution
- Mar 24, 2016.
The naysayers are on the wrong side of "citizen" Data Scientist debate. Business users already have self-service BI capabilities and make decisions whether they are statistically sound or not. We can’t stop them from making decisions but should make statistically sound decisions easier. This new approach is called Smart Data Discovery.
- When Big Data Means Bad Analytics
- Mar 21, 2016.
When analytics delivers disappointing results, it is often because there is not enough analytic expertise, and/or lack of understanding of a business objectives for using Big Data in the first place. To avoid failure, insist on high standards.
- AlphaGo is not the solution to AI
- Mar 21, 2016.
The field will be better off without an bust cycle it is important for people to keep and inform a balanced view of successes and their extent. AlphoGo might be a step forward for the AI community, but it is still no way close to the true AI.
- Analytics Hiring Strong, Staying In One Job Is Weak
- Mar 21, 2016.
With more companies jumping on the data-driven bandwagon, companies have been creating new roles and new data science and analytics teams. It is right time to make your move and land up in your dream job.
- 3 Telecom Developments Which impact IoT Analytics
- Mar 18, 2016.
Highlights and developments to watch from Mobile World Congress 2016 which will impact IoT analytics in future.
- Big Data Will Rule Your Home
- Mar 18, 2016.
The "connected home" is the next frontier for Big Data, and soon our lives may be significantly impacted by the analytical firepower from the IoT. Would benefits outweigh the risks and how would you then feel if your fridge locks you out because your scales and wearables have sounded the warning signs?
- Exclusive Interview with Alexander Gray, Skytree CEO: Fast, Automated, Machine Learning Software for Free?
- Mar 17, 2016.
We discuss how Skytree compares with competition, how does it perform relative to expert Data Scientists, how does Skytree Automodel compare to Deep Learning, and more.
- Data is the New Everything
- Mar 17, 2016.
Data gets a lot of mainstream attention these days, and has been compared to all sorts of different things. This is a lighthearted look at some of the top suggestions from Google autocomplete when searching for the phrase "data is the new" something.
- The Evolution of the Data Scientist
- Mar 16, 2016.
We trace the evolution of Data Science from ancient mathematics to statistics and early neural networks, to present successes like AlphaGo and self-driving car, and look into the future.
- Career Advice to Data Scientists – Go Make More Money
- Mar 16, 2016.
Data Scientist should offer the enterprise more than the ability (and cost) of doing analysis, but behave as an executive with expertise in analysis and help lead the enterprise on decisions, investments, and operations.
- After 150 Years, the ASA Says No to p-values
- Mar 15, 2016.
The ASA has recently taken a position against p-values. Read the overview and opinion of a well-respected statistician to gain additional insight.
- Wind and Weather – Open Text Data Digest
- Mar 15, 2016.
It’s soothing to watch the wind flows cycle and clouds form and dissipate. Now an app called Windyty lets you navigate real-time and predictive views of the weather yourself, controlling the area, altitude, and variables such as temperature, air pressure, humidity, clouds, or precipitation.
- How to tell a great analyst from a good analyst
- Mar 15, 2016.
Good analyst help businesses to stay in the competition, but great analyst sets the business apart from its competition. Learn more about how to be a great analyst by walking that extra mile.
- What Should Data Scientists Know About Psychology?
- Mar 14, 2016.
Due to training in the scientific method, data management, statistics/data analysis, subject matter expertise, and communicating results into substantive knowledge psychology researchers must have a solid understanding of data science and vice-versa.
- The Anchors of Trust in Data Analytics
- Mar 14, 2016.
An exploration of some of the critical questions and challenges emerging around trust in data and analytics. The four anchors of trust that will shape public confidence in D&A in the age of the analytical enterprise are highlighted.
- When Good Advice Goes Bad
- Mar 14, 2016.
Consider these 4 examples of good statistical advice which, when misused, can go bad.
- What is the influence of Big Data in Medicine?
- Mar 14, 2016.
The 360-degree customer view is the idea, that companies can get a complete view of customers by aggregating data from the various touch points that a user. And, big data is helping to materialize this idea, which will revolutionize the healthcare.
- Fraud Bots Mess Up Your Big Data
- Mar 11, 2016.
The bots that cause digital ad fraud also mess up analytics. When they create fake visits, pageviews, ad impressions, clicks, etc. those metrics are not real and should be corrected for.
- The Data Science Puzzle, Explained
- Mar 10, 2016.
The puzzle of data science is examined through the relationship between several key concepts in the data science realm. As we will see, far from being concrete concepts etched in stone, divergent opinions are inevitable; this is but another opinion to consider.
- Practical Career Advice and Best Practices in Analytics
- Mar 10, 2016.
Being an analyst is not only a technical job it also has a peoples side to it. Given that many MBAs, engineers, and even non-quantitative graduates are interested in Analytics careers, we are sharing some advice on best practices for excelling with Analytics in your career.
- The Data Science Process, Rediscovered
- Mar 9, 2016.
The Data Science Process is a relatively new framework for doing data science. It is compared to previous similar frameworks, and a discussion on process innovation versus repetition is then undertaken.
- Deep Learning: an Interview with Yoshua Bengio
- Mar 8, 2016.
Yoshua Bengio is a renowned figure in the machine learning and specifically deep learning, here is an interview with Yoshua about his thoughts on media interest in the field, future developments and more.
- Fastest Growing Programming Languages and Computing Frameworks
- Mar 7, 2016.
A new model for ranking programming languages and predicting the growth of user adoption. Includes current language rankings and predictions.
- Trump vs Clinton – What are the Odds?
- Mar 7, 2016.
Even with 5% advantage for Clinton, statistical analysis and examining how undecided break towards these candidates, we estimate a 25%-30% chance that Trump would be elected president.
- Nurture by Numbers – Big Data and Children
- Mar 5, 2016.
Driven by rising healthcare costs and competitions for top schools, more organisations and individuals are turning to Big Data and Analytics to try and give their children the upper hand.
- The Rise Of The Robot
- Mar 3, 2016.
Atlas, the latest robot from Google's Boston Dynamics a pretty resilient chap. He can trudge through uneven snow, be knocked off his feet and get up again. and do work that can take place in any warehouse. We examine what it means for our future.
- The Mirage of a Citizen Data Scientist
- Mar 1, 2016.
The term "citizen data scientist" has been irritating me recently. I explain why I think it both a bad term and a bad idea, and what we need instead.
- Dynamic Data Visualization with PHP and MySQL: Election Spending
- Mar 1, 2016.
Learn how to fetch data from MySQL database using PHP and create dynamic charts with that data, using an interesting example of New Hampshire primary election spending.
- Data Science and Disability
- Mar 1, 2016.
Data Science and Artificial Intelligence has come to the forefront of technology in the last few years. Learn, how practitioners are taking a more philanthropic outlook on life, supporting people suffering with both physical and mental disabilities.
Learn Deep Learning with this Free Course from Yann LeCun
TabPy: Combining Python and Tableau