GitHub and Reddit are two of the most popular platforms when it comes to data science and machine learning. The former is an awesome tool for sharing and collaborating on codes and projects while the latter is the best platform out there for engaging with data science enthusiasts from around the world. This year, we have covered the top GitHub repositories each month and from this month onwards, we will be including the top Reddit threads as well that generated the most interesting and intriguing discussions in the machine learning space. April saw some amazing python libraries being open sourced. From Deep Painterly Harmonization, a library that makes manipulated images look ultra realistic, to Swift for TensorFlow, this article covers the best from last month.
Of all the trends that have made headlines over the last few years, none has had a greater impact than the rise of Big Data. Businesses, news agencies, police stations, nonprofits, nearly every organization you can think of are gathering and using data to change how they operate from day to day. Ideally, they're using all this data to make better decisions, taking into account a larger and broader pool of information so as to avoid common sources of mistakes and biases. But as valuable as Big Data is, simply having it is no guarantee that your organization will make better decisions. Data can help you understand what's happening at your company and what it means for the future, but only if you have the tools to interpret it.
Vimarsh Karbhari(VK): What are the top three books about AI/ML/DS have you liked the most? What books have had the most impact in your career? VK: What tool/tools (software/hardware/habit) that you have as a Data Scientist has the most impact on your work? Github because it allows all of my code to be in one place and allows me to share it with my team members (along with use some of their code in my work). It also allows version control, code reviews, and a backup for my code.
Recently, Spotify, a global music content platform, introduced a new feature, Discover Weekly, as an intelligent playlist developer for its users. Based on a listener's past history, preferences and the trends reflected by analysing data from music aficionados with similar tastes, the company implemented machine learning'best fit' algorithms to provide its users with a delectable list of latest music that kept them glued to their headphones for hours. This is one of the many instances where AI has transformed customer experience as we know it. The two most popular vowels on the internet, AI or Artificial Intelligence, are being implemented by various industries to learn from data, identify the most efficient operational processes and go beyond passive advertisements to enhance the customer engagement quotient. In fact, a report by Servion predicts that AI will power 95 per cent of all customer interactions by 2025.
I am doing a video analysis A.I. project for a client, and I want to share with you a super fun idea that popped into my mind tonight while I was waiting for stuff to render. I really don't have time to be writing this, but I feel like I have to. Some ideas are just too awesome to not stay up all night programming. Let's get an A.I. system to outline people in a music video. There have been some great object detection articles on Towards Data Science, and so I don't want to post duplicates of the same cool stuff.
South Africa is facing a shortage of data scientists – a new breed of analytical data experts with the technical skills to solve complex problems. They're part mathematician, part computer scientist and part trend-spotter. And, because they straddle both the business and IT worlds, they're highly sought-after and well paid. The demand for data scientists is being driven by the emergence of big data – that unwieldy mass of unstructured information that can no longer be ignored and forgotten. It's a potential gold mine for companies – as long as there's someone who can dig in and unearth the business insights that no one thought to look for before.
The Bank of England's chief economist, Andy Haldane, has urged his colleagues to examine the musical mood of the nation when contemplating changes to the Bank's interest rate. How could an increase in Taylor Swift downloads or a decline in the popularity of rock and roll be relevant for managing the economy? It all comes down to measuring economic sentiment. This is a way of gauging how people feel about the economy, which behavioural economists use to make predictions about how it will respond to different policies. For example, if people are generally pessimistic about the economy then raising interest rates might encourage them to stop borrowing and spending by so much that it harms the economy.
China's first virtual reality (VR) theme park opened near Guiyang, the provincial capital of Guizhou. The park features 35 virtual attractions -- instead of getting on a roller coaster, you don VR goggles -- but there is a spectacular physical construction, too: a 53-meter-tall, 700-ton statue of a robot. You can watch a CGTN video report on Oriental Science Fiction Valley, or read these reports on the park from Reuters and Kotaku. Guizhou, one of China's poorest provinces, is perhaps most famous for Lao Ganma 老干妈 spicy sauce and Maotai, the sorghum-based spirit that lubricated Richard Nixon's visit to China in 1972. But the VR theme park is just the most recent manifestation of an initiative to drastically change Guizhou's economy and image, with support from the very top:
Some movies are obvious hits. Like, for example, Avengers: Infinity War, which made a record-breaking $258 million at the domestic box office last weekend, filling seats and the pockets of Marvel Studios parent company Disney. But not every summer--or spring, or fall--blockbuster has the benefit of 10 years and 18 movies of built-up audience goodwill. So while the Mouse House knew they had a potentially earth-shattering hit on their hands well before opening night, other studios trying to catch up have no way of predicting whether their latest attempts to hit big will do so. Machine learning is everywhere, and artificial intelligence is no longer just a Spielberg-Kubrick collaboration.