Machine learning in finance may work magic, even though there is no magic behind it (well, maybe just a little bit). Still, the success of machine learning project depends more on building efficient infrastructure, collecting suitable datasets, and applying the right algorithms.Machine learning is making significant inroads in the financial services industry. Let’s see why financial companies should care, what solutions they can implement with AI and machine learning, and how exactly they can apply this technology.DefinitionsWe can define machine learning (ML) as a subset of data science that uses statistical models to draw insights and make predictions. The chart below explains how AI, data science, and machine learning are related. For the sake of simplicity, we focus on machine learning in this post.The magic about machine learning solutions is that they learn from experience without being explicitly programmed. To put it simply, you need to … [Read more...] about Why financial companies should care about machine learning?
Machine learning examples in real life
Video: GDPR: US companies with no physical presence in EU still need to comply GDPR is finally here, and it's here to stay. The 25th of May is not the finish line; it's really only the beginning. GDPR's impact will be felt across the board and across the world. ZDNet discussed with a wide range of experts, aiming to decipher the real-life applicability and impact of GDPR. Read also: GDPR is already a success, whether you like it or not In the first part, we looked into the reasons why most organizations are not ready to deal with GDPR, the chances of US-based organizations being scrutinized under GDPR, and the process and expectations for individuals wishing to exercise their rights under GDPR. We now continue with GDPR audits on premise and in the cloud, its impact on innovation, machine learning, and interpretable artificial intelligence, as well as how GDPR goes well across borders and organizations and into the future.Auditing data on premise and in the cloud So, … [Read more...] about GDPR in real life: Transparency, innovation, and adoption across borders and organizations
May 8, 2018 - Written By Kristijan Lucic Google had introduced “Google Lens” last year, and during its keynote at this year’s Google I/O, the company announced some new features for it, plus some other Google Lens-related news. Let’s start with the fact that Google Lens is coming to camera apps on supported devices from LG, Motorola, Xiaomi, Sony Mobile, HMD/Nokia, Transsion, TCL, OnePlus, BQ, ASUS, and the Google Pixel, of course.Now, as far as features are concerned, “Smart Text Selection” has been added. This feature will basically let you select text from an image, from a recipe, for example, or some paper that you took a picture of. After you select it, you can copy / paste it in Google Search, share to a friend, or whatever else you find fit, as you would with text selected from a digital document. The second feature Google announced is “Style Match”. If you ever wanted to find similar home decor or outfit ideas based on something … [Read more...] about Google Lens Now Works In Real Time, Gets New Features – Google I/O
Artificial intelligence and machine learning are terms which have been thrown around a lot in the tech industry over the last few years, but what exactly do they mean? Anyone vaguely familiar with sci-fi tropes will probably have an idea about AI, though they may view it as a little more sinister than what’s around today. The two terms are often conflated and, incorrectly, used interchangeably, particularly by marketing departments that want to make their technology sound sophisticated. In fact, artificial intelligence and machine learning are very different things, with very different implications for what computers can do and how they interact with us. It starts with Neural Networks Machine learning is the computing paradigm that’s lead to the growth of “Big Data” and AI. It’s based on the development of neural networks and deep learning. Typically this is described as imitating the way humans learn, but that’s a bit of a misnomer. … [Read more...] about Artificial Intelligence vs Machine Learning: what’s the difference?
Machine learning is still a pipe dream for most organizations, with Gartner estimating that fewer than 15 percent of enterprises successfully get machine learning into production. Even so, companies need to start experimenting now with machine learning so that they can build it into their DNA.Easy? Not even close, says Ted Dunning, chief application architect at MapR, but “anybody who thinks that they can just buy magic bullets off the shelf has no business” buying machine learning technology in the first place.“Unless you already know about machine learning and how to bring it to production, you probably don’t understand the complexities that you are about to add to your company’s life cycle. On the other hand, if you have done this before, well-done machine learning can definitely be a really surprisingly large differentiator,” Dunning says.Open source projects like TensorFlow can dramatically improve an enterprise’s chances of machine … [Read more...] about TensorFlow machine learning: What to know before you get started