How can you get better performance from your deep learning model? It is one of the most common questions I get asked. What can I do if my neural network performs poorly? I often reply with "I don't know exactly, but I have lots of ideas." Then I proceed to list out all of the ideas I can think of that might give a lift in performance. Rather than write out that list again, I've decided to put all of my ideas into this post. The ideas won't just help you with deep learning, but really any machine learning algorithm. How To Improve Deep Learning Performance Photo by Pedro Ribeiro Simões, some rights reserved. This list of ideas is not complete but it is a great start.

Investments in the future will be based on algorithms and patterns charted by robot. Emerging as one of the hot sectors in fintech, robo-advisory can come across as the next big disruption in the space. According to YourStory Research, there are close to 50 Indian early-stage startups flocking around this sector. A Deloitte research paper states that the top 11 firms in this segment globally have seen explosive growth since market entry, managing close to 19 billion Assets Under Management (AUM) in 2014. This disruption in the personal wealth management space is called robo-advisory, which leverages client information through algorithms, automating and recommending tailored investments to individuals.

Sony's new a6500 and RX100 V and their blazing fast burst modes and impressive autofocus specs have prompted The Verge's Sean O'Kane to declare that we're living through nothing short of a revolution in photography: Quality aside, this type of feature is changing the basic exercise of photography, which is to capture a subject in a particular moment. This idea was famously framed by French photographer Henry Cartier-Bresson as "the decisive moment." It's the kind of tenet that gets beaten into the heads of anyone who takes photography classes in grade school and college, and it is on the verge of being wiped out by the pace of technology….we A photographer equipped with a camera like the RX100 Mark V will still have to anticipate the right moment to start firing, but there's far more room for error than ever before. "Spray and pray" is nothing new and what Sony has done is arguably less revolutionary than evolutionary–they've refined and improved upon an existing concept. And O'Kane is unquestionably right.

Deep learning is becoming increasingly used throughout the world of technology, and there are now endless blogs, books, courses and other resources available for those to use. If that's still not quite good enough for you and you don't want to implement deep learning yourself, there are now several machine learning API services available that will do it for you. But, where has this rise in deep learning stemmed from you may be wondering? Big companies use deep learning techniques in various practices throughout their businesses. They generate lots of data, and this is mega important to them as they can learn from this data which will ultimately lead to increased revenue.

In an attempt to make medical diagnoses easier and help both patients and doctors, Chinese search engine company Baidu has announced the launch of Melody, a medical assistant chatbot powered by artificial intelligence (AI). Reported on by VentureBeat, Melody can be found in Baidu's existing Baidu Doctor app for Android and iOS where she will collect medical information from patients before passing it on to doctors. The chatbot has been developed to ask questions on important health factors such as age and symptoms, before passing the answers on to doctors in an easy-to-use form. Doctors can then proceed with their diagnosis and respond to patients, reducing the amount of time that patients and medical professionals spend exchanging basic information. To make sure information is accurate, Melody only sends responses on behalf of doctors after the doctors have verified it, with Baidu chief scientist Andrew Ng commenting in an interview with VentureBeat that, "It's not our role to diagnose -- it's the doctors' role to diagnose. We try to assist the doctors."

Amazon, Facebook, Google, IBM and Microsoft pledged to address the privacy, security and ethical challenges of AI. NEW YORK -- Five leading tech companies launched a new effort Wednesday to head off government regulation of artificial intelligence, the fast-growing field at the heart of self-driving cars, digital assistants and other emerging technologies. Through the so-called Partnership on Artificial Intelligence, Amazon, Facebook, Google, IBM and Microsoft pledged to address the privacy, security and ethical challenges of AI -- by funding new research and setting up industry best practices -- as they invest heavily in complex algorithms that can understand human speech or comb through vast amounts of data. "The positive impacts of AI will depend not only on the quality of our algorithms, but on the level of public engagement," said Mustafa Suleyman, the co-founder of DeepMind, an artificial intelligence company purchased by Google, and a co-chair of the new group. He and other leaders, speaking with reporters Wednesday, said the technology could reduce traffic congestion, tackle climate change and more.

While the number of available jobs is rising, workers' skills and technology-driven jobs may be at odds. Here's what societies could do to address the impact that automation and artificial intelligence may have on labor. When Ken Jennings was defeated by IBM's Watson on the TV show Jeopardy! As someone with a degree in computer science, several million in winnings, and still considerable social media presence, he can perhaps afford to be sanguine. Will advancements in technology, automation and artificial intelligence threaten our jobs?

Entrepreneurs need little convincing that technology is important, rapidly evolving, and likely to have a profound impact on their businesses. But keeping track of developments, and knowing where to focus one's attention, is anything but straightforward. Analysts at PricewaterhouseCoopers (pdf) say the impact of constant technological breakthroughs represent a "megatrend" – a change so big that "every business should develop an emerging technology strategy". They have highlighted eight key areas that all businesses should pay attention to. The artificial intelligence market is growing rapidly and forecast to be worth 36bn by 2025.

The recent progress in Artificial Intelligence and Machine Learning makes questions about the ethics of AI more pressing than ever. Most tech companies and their employees want to do good in the world. We all have an image of our better selves or "at our best." We also want to avoid the risks that come with the increasing public scrutiny of ethical lapses. The main idea behind Humans & Machines Ethics Canvas is to have a blueprint from ideation to successful completion of the project for individual, teams and organisations.

Mobile broadband operators are ramping up spend for big data and machine learning as they transform into digital service providers. With a long history of handling huge datasets, and with their path now blazed by the IT ecosystem, mobile operators will devote more than 50 billion to big data and machine learning analytics through 2021, forecasts ABI Research. Machine learning technologies will lead operators to profoundly change how they manage the telecom business. "Machine learning-based predictive analytics are applicable to all aspects of the telecom business," says Joe Hoffman, Managing Director and Vice President at ABI Research. "It is important that operators master and internalize these technologies and not rely solely on their vendors' expertise. Executives that overlook big data and machine learning risk irrelevance."