Added by Vozag on August 6, 2015 at 9:30pm — No Comments
Alan Turing was the first one to present the idea of simulating the machine thinking. Its been more than 60 years since the ground breaking paper of Alan Turing came out, The Imitation Game. The world has changed rapidly since then.
The machines of today have become so powerful. They can actually think, which endorses the idea of Alan Turing presented in 50s. However, the machine thinking may be different. Alan Turing argued, just because the thinking can be…Continue
Machine learning isn't a set-it-and-forget-it operation. Even with solid examples, ML algorithms can still fail and end up blocking important emails, filtering out useful content, and causing a variety of other problems.…Continue
Added by Renette Youssef on February 5, 2015 at 10:30am — No Comments
The purpose of Financial Modeling is to build a Financial Model which can enable a person to take better financial decision.The decision could be affected by future cash flow projections , debt structure for the company etc. All these factors may affect the viability for a project or investment in a company.The Applications of Financial Modeling mainly includes the followings :
Added by rajesh dhnashire on January 26, 2015 at 11:00pm — No Comments
We’ve created a Domino project with starter code in R and Python for participating in the Data Science Bowl.
Get a jump start in the competition with our starter project by training your models on massive hardware and running multiple experiments in parallel while keeping track of…Continue
Added by Anna Anisin on January 13, 2015 at 3:00pm — No Comments
We all know that calculating error bounds on metrics derived from very large data sets has been problematic for a number of reasons. In more traditional statistics one can put a confidence interval or error bound on most metrics (e.g., mean), parameters (e.g., slope in a regression), or classifications (e.g., confusion matrix and the Kappa statistic).
For many machine learning applications, an error bound could be very important.…Continue
Added by Anna Anisin on December 14, 2014 at 3:33pm — No Comments
When you use Twitter, how do you know when you are being presented with something credible instead of something totally bogus? The answer is, unless you spend a lot of time researching each tweet, you probably don’t. However, one thing is for certain, we rely on what we read on Twitter to be true.
Twitter is one of the fastest and most effective ways we disseminate news across our world. If this…Continue
Added by Renette Youssef on December 8, 2014 at 4:00pm — No Comments
As humans, we navigate our lives largely by the recognition of patterns. These patterns include the sound of a mother’s voice, the appearance of a dangerous animal or poisonous food, the familiarity of kin, and the attraction to potential mates. Accurate pattern recognition is key to an animal’s survival and progress, and has allowed humans to become the socially complex and advanced species we are today.
It should come as no surprise that…Continue
Added by Sean McClure on September 29, 2014 at 9:01am — No Comments
This blog is extrapolated from DataScience Hacks by the author himself.
Apache Spark, another apache licensed top-level project that could perform large scale data processing way faster than Hadoop (I am referring to MR1.0 here). It is possible due to Resilient Distributed Datasets concept that is behind this fast data processing. RDD is basically a collection of objects,…Continue
Added by derick.jose on June 17, 2014 at 2:00am — No Comments
I've always been interested in data, how it's interpretted and the different ways it can be sliced. However, I've always considered statstics itself to be a math that I didn't like. As "data science" and "big data" became more popular, however, I started to look into ways to learn more about it and possibly use it as a entry into another act of my career.
The advent of MOOCs has opened up the possibility of learning new subjects and subject-focused websites like Data Science Central…Continue
If I want to build a house, wouldn't it be wise to learn carpentry? Does the analogy hold for data-analytic multivariate models? Or is it simply enough to let a machine do it, with no knowledge by the machine operator of how to interpret the results from those modeling efforts? Or is it true, as one person has recently asserted, that he could replicate ALL statistical procedures and techniques using MapReduce, without knowing anything about statistics and probability, or the vast collection…Continue
Data science might be one of the hottest buzzwords in 2013. But is it only a marketing gimmick? I don’t think so. In my opinion, data science can be the best protocol that reveals what’s happening every day in the real world.
The data science incorporates mathematics, statistics, computer science and…Continue
Added by Yuanjen Chen on February 6, 2014 at 6:30pm — No Comments
Smart organizations are using the power of data science and data produced by embedded sensors and machine devices to better measure performance, discover patterns, prevent problems, and improve…Continue
Practicing Data science indeed a long term effort than a learning handful of skills. We ought to be academically good enough to take up this challenge. However, if you think you came a long way from your academic rebuilding, but you still have that zeal & passion to take the oil from the data and fill the skill gap of data science then here is the warm-up tips. Below points must exercised before jumping into…Continue
Added by Manish Bhoge on October 18, 2013 at 9:26am — No Comments
One of the most popular methods or frameworks used by data scientists at the Rose Data Science Professional Practice Group is Random Forests. The…Continue
High Performance Computing (HPC) plus data science allows public and private organizations get…Continue
Data Science - The Process of Capturing, Analyzing and Presenting Business Intelligence with Skill - DataReality