Hi All, I would like to guidance on Machine Learning for text prediction. I have large amount of data, around 10GB of SNMP traps weekly coming through SNMPTT and manipulated and exported to multiple databases, sql, elasticsearch etc.. and wondering what framework the group would recommend I spend my time on for SNMP trap prediction.

I am a self taught coder for the past 6 months. When I apply for jobs, I keep getting rejected as I was told i have no portfolio to show and i dont have a software engineering background so why hire me when they can hire an experienced software engineer and train him on machine learning skills. I am getting depressed over this situation over the past few weeks and considering looking for jobs in my previous non-tech related job field. So kindly, please provide me with an interesting project that can allow me to showcase my skills. I am also willing to do free projects for anyone out there as long im guided on the best practices.

Media attending the event included BBC News, The Guardian, The Wall Street Journal, Bloomberg, VentureBeat, Digital Trends, Financial Times, Ars Technica and more. News coverage focused on a range of topics, exploring advancements in robotics, chatbot personalities, machine vision for understanding differences in language and culture, as well as startup acquisitions and funding. We've shared just a few of the great articles from the summit below. Why Data is the New Coal - The Guardian Deep learning needs to become more efficient if it is going to move from using data to categorise images of cats to diagnosing rare illnesses. Alex Hern reports on revelations in this area from speaker Neil Lawrence, the newly appointed Senior Principal Scientist at Amazon.

I see, well I'm trying to achieve (in regards to the project) exactly what I said before. The title of the project is "Reusable Machine Learning components" and I'm aiming to implement the algorithms above. As long as it works it's fine. What I'm trying to get out of it personally, is to deepen my understanding of some of the common machine learning algorithms and learn as much as I can in the process (plus get a good mark). Also if I could learn skills that mimic what would be done in the industry.

Does anyone know of experiments with using y in multiple locations in a neural network (using back-propagation)? Might it not be another solution for short-term vs long-term issue? E.g. some nodes are allowed short access to y and some are having a larger distance to y, generating more complex features.

Josh Fischel, the founder of last weekend's inaugural Music Tastes Good Festival in Long Beach, died Thursday afternoon of liver disease, according to festival organizers. The news came as a shock to the Long Beach and Southern California music communities, who just days ago saw Fischel overseeing the culmination of a life's work in local music. Though family and festival organizers knew he had been sick, no one knew how rapidly his disease would progress after the festival. Music Tastes Good was a three-day event in downtown Long Beach headlined by the likes of the Specials, Warpaint and the Squeeze, among many others. "He couldn't go more than a few feet in his golf cart without somebody stopping him to say'Hey, Josh!' " said Jon Halperin, the talent buyer and co-promoter of Music Tastes Good.

Will "Miss Peregrine's Home for Peculiar Children" have a fairy-tale ending at the box office? While its final chapter has yet to be written, Tim Burton's fantasy film is earning pretty good grades at the multiplex so far. The picture about a group of extraordinary children collected 9 million on Friday, according to an estimate from distributor 20th Century Fox. That means the movie is on track to gross around 27 million by weekend's end -- a so-so start, considering the picture cost the studio 110 million to make. The weekend's other big debut, "Deepwater Horizon," lagged slightly behind in ticket sales Friday, with 7.1 million.

That has been its brand since the days of "It's not television, it's HBO." Television eventually caught up, which meant HBO had to swing bigger; it is not built for, or on, a slate of solid but not spectacular shows. It is a premium cable channel, which means it needs to bring the premium. So when an HBO series fails -- "Vinyl," "Luck," "John From Cincinnati" -- it fails hard. But when it connects, well, hits like "Game of Thrones" and "Veep," "Last Week Tonight With John Oliver" and "Olive Kitteridge" don't just sweep up Emmys, they change the nature of television.

Research in artificial intelligence (AI) is known to have impacted medical diagnosis, stock trading, robot control, and several other fields. Perhaps less popular is the contribution of AI in the field of music. Nevertheless, Artificial intelligence and music (AIM) has, for a long time, been a common subject in several conferences and workshops, including the International Computer Music Conference, the Computing Society Conference and the International Joint Conference on Artificial Intelligence.

At Sundance earlier this year, the absurdist comedy "Swiss Army Man" rubbed so many critics and audience members the wrong way that it provoked mass walkouts and angry pans. But once the film moved from the festival circuit to the arthouse, it found an audience much more receptive to writer-directors Daniel Scheinert and Daniel Kwan's gently twisted sense of humor. A combination of Robert Bresson and "Weekend at Bernie's," "Swiss Army Man" stars Paul Dano as a suicidal castaway who finds a flatulent corpse (played by Daniel Radcliffe) on the shore of a deserted island. He uses the dead man as a tool, a companion and an inspiration to survive. Filled with raunchy jokes and positive vibes, this is a movie that'll baffle some viewers, but it's such an original that it's hard not to admire.