There’s gold in that mountain! The need is to get the right tool to dig it. For many today, that right tool is called Deep Learning.
Today, the realms of business, science, and technology are merging together like never before. The amount of data thus available to us has outstripped our tools for analyzing and using them. This leads to a mountain of unstructured data waiting to be tapped. There’s gold in that mountain! The need is to get the right tool to dig it. For many today, that right tool is called Deep Learning.
Deep Learning: What is it?
Deep learning, which was first theorized in the early 80's (and perhaps even earlier), is one paradigm for performing machine learning. And because of a flurry of modern research, deep learning is again on the rise because it's been shown to be quite good at teaching computers to do what our brains can do naturally- learn through examples and experiences. Programmers develop algorithms that software applications can use to study many examples and then use the acquired “learning” to solve the problem. In other words, the algorithm is teaching the computer to solve by example. The whole objective of Deep Learning is to solve problems with no set rules.
Deep Learning vs Traditional Machine Learning
Sometimes, we encounter problems for which it’s very hard to write a computer program to solve it. Recognizing hand-written digits, recognizing objects, understanding concepts, comprehending speech, are some such tedious problems. This is because it becomes quite complicated to compile a list of heuristics that accurately classify different sample sets for each of these problems. This trouble is faced with traditional machine learning models, and is called a feature extraction.
Feature extraction involves the need for the programmer to specifically tell the computer what kind of things it should be looking for that will be informative in making a decision. This places a huge burden on the programmer, and the algorithm's effectiveness relies heavily on how insightful the programmer is.
Deep learning is one of the only methods by which we can circumvent this challenge of feature extraction. This is because the deep learning model enables machines of learning to focus on the right features by themselves, requiring little guidance from the programmer. This makes deep learning an extremely powerful tool for modern machine learning.
How Deep Learning can Impact your Business
Some of the industry sectors reaping benefits of Deep Learning are:
Oil and Gas: When Deep Learning technology intersects with abundant oil and gas seismic data, the outcome could yield a more accurate depiction of what lies beneath the surface, enabling cash-strapped drillers to better target sweet spots and maximize returns. There will be more and more need for cheap and environmentally friendly energy. Cutting edge technology like Deep Learning will help identify and maximize efficiency in development of natural resources and keep the process as safe as possible for the surrounding environment.
Banking: Banks are being hacked all the time. According to various statistics, banks get over a million cyber attacks a year, and protecting the bank from a breach is getting harder and harder. Deep Learning assumes importance here by building intelligence into the network. In other words it will enable banks, payment processors and other financial firms to soon move into real-time analytics and artificial intelligence techniques to crack down on fraud.
Finance: Decreasing margins and continuing economic uncertainty are two major roadblocks in this sector. Fortunately, both these problems can be tackled with the right information. Setting prices, assessing performance, segmenting customers and measuring their satisfaction requires predictive analysis. Legacy methods will fail to do so. Deep Learning is the only way out!
Sales: For much of history, the trick of sales has been finding the best people to pitch your product to. Successful companies are using Deep Learning to answer the question “Who are the people that matter?”, thus enabling smart sales teams to exceed their targets.
Some of the well-known companies already utilizing Deep Learning technologies include Apple, Facebook, Google, IBM, Microsoft, PayPal, Pinterest, Twitter, Yahoo and others.
So whatever be your line of business, Deep Learning model helps you maximize your ROI, and keeps you ahead of your competitors.
Source: http://andrewyuan.github.io/
