Dropout means to drop out units which are covered up and noticeable in a neural network. Dropout is a staggeringly in vogue method to overcome overfitting in neural networks.
Deep Learning framework is now getting further and more profound. With these bigger networks, we can accomplish better prediction exactness. However, this was not the case a few years ago. Deep…Continue
Added by saurav singla on July 28, 2020 at 12:12am — No Comments
Added by Robert R. Tucci on December 17, 2019 at 12:00pm — No Comments
Summary: In the literal blink of an eye, image-based AI has gone from high cost, high risk projects to quick and reasonably reliable. C-level execs looking for AI techniques to exploit need to revisit their assumptions and move these up the list. Here’s what’s changed.
For data scientists these are miraculous times. We tend to think of miracles as something that occurs instantaneously but in our world that’s not quite so. Still the rate…Continue
Added by William Vorhies on March 4, 2019 at 9:41am — No Comments
For most businesses, machine learning seems close to rocket science, appearing expensive and talent demanding. And, if you’re aiming at building another Netflix recommendation system, it really is. But the trend of making everything-as-a-service has affected this sophisticated sphere, too. You can jump-start an ML initiative without much investment, which would be the right move if you are new to data science and just want to grab the low hanging fruit.
One of ML's…Continue
Added by Olexander Kolisnykov on September 18, 2018 at 2:52am — No Comments
The insurance industry – one of the least digitalized – is not surprisingly one of the most ineffective segments of the financial services industry. Internal business processes are often duplicated, bureaucratized, and time-consuming. As the ubiquity of machine learning and artificial intelligence systems increases, they have the potential to automate operations in insurance companies thereby cutting costs and increasing productivity. However, organizations have plenty of reasons to resist…Continue
Added by Denys Harnat on August 28, 2018 at 3:35am — No Comments
The best trained soldiers can’t fulfill their mission empty-handed. Data scientists have their own weapons — machine learning (ML) software. There is already a cornucopia of articles listing reliable machine learning tools with in-depth descriptions of their functionality. Our goal, however, was to get the feedback of industry experts.
And that’s why we interviewed data science practitioners — gurus, really —regarding the useful tools they…Continue
Added by Kateryna Lytvynova on July 13, 2018 at 2:00am — No Comments
Added by Serge Audenaert on April 25, 2018 at 10:30pm — No Comments
Cambridge Analytica’s wholesale scraping of Facebook user data is big news now, and people are “shocked” that personal data is being shared and traded on a massive scale on the internet. But the real issue with social media is not harm to individual users whose information was shared, but sophisticated and sometimes subtle mass manipulation of social and political behavior by bad actors, facilitated by deceit, fraud, and amplification of lies that spread easily through societal…Continue
Should a true AI engine be industry focused or industry neutral to have a positive effect on company valuation? This is one of the key debates amongst the VCs & PE firms evaluating their investment options in the promising world of AI startups.
Technology startups are often categorised by analysts…Continue
Added by Mukul Gupta on November 7, 2017 at 8:30am — No Comments
Added by Salman Khan on May 25, 2016 at 5:00am — No Comments
I attended the Carrier Network Security Strategies conference ( #CNSS2015)held by Light Reading in NYC on Dec 2. I also attended the New Jersey Tech Council’s Data Summit (#NJTechCouncil) on Dec 9. The main topics of discussion in the conference were around securing the perimeter of networks and protecting customer, carrier and network data. Here is brief summary of what I learned in these two conferences about managing and operating networks securely and protecting…Continue
Added by Srividya Kannan Ramachandran on December 14, 2015 at 8:00am — No Comments
Analyse TB data using network analysis
In a very interesting publication from Jose A. Dianes on tuberculosis (TB) cases per country it was shown that dimension reduction is achieved using Principal Component Analysis (PCA) and Cluster Analysis (…Continue
As the size of the database grows database performance becomes critical. Automation is a growing focus for data center operators facing increasingly complex environments. Database administration is complex, repetitive and time consuming. DBAs have to work long hours during off hours downtime. The outage of database costs heavily to the companies and affect their repute.
Shopping engines and online shopping places are highly dependent on database performance. Slower application…Continue
Added by Muhammad Saeed on May 9, 2014 at 4:00am — No Comments