Developed by Minderoo Foundation, the'Global Plastic Watch' tool uses advanced satellite data technology and machine learning to create a near-real-time, high resolution map of plastic pollution. The tool aims to help authorities better manage plastic leakage into the marine environment, and is said to provide the largest ever open source dataset of plastic waste across dozens of countries. Global Plastic Watch uses remote sensing satellite imagery from the European Space Agency and a novel machine learning model created in collaboration with digital product agency Earthrise Media. The tool can determine the size and scale of land-based plastic waste sites, which fuel the growing issue of plastic pollution in the world's rivers and oceans. By using the data, governments, industry and communities can evaluate and monitor the risk of land-based plastic waste sites as well as prioritise investment in solutions, Minderoo Foundation said.
The Indian Institute of Technology (IIT), Roorkee is offering a five-month online course on data science and machine learning (ML). The course is conducted by Imarticus Learning in association with iHUB DivyaSampark to enable candidates to leverage data Science and ML for effective decision-making. Prof Sudeb Dasgupta, project director of iHUB DivyaSampark said in a press release, "We bring iHUB DivyaSampark's expertise in building outstanding programs with IITs and Imarticus' technical expertise to deliver an outstanding learning experience through a holistic approach. Together, we envision creating a skilled workforce for innovation and digital growth." For more information, go through the brochure.
There's no lack of startups around the world trying to make industrial activities more efficient with artificial intelligence. Some invent robots to assist or replace manual labor, while others use machine learning to help businesses discover insights. Synergies Intelligent Systems falls into the second category. Michael Chang founded Synergies in 2016 in Boston to provide easy-to-use AI-powered analytics tools to medium-sized manufacturers. Having worked at Foxconn in Shenzhen in the late 2000s helping the Apple supplier improve yield rate, or reduce the percentage of defective products, using data analysis, Chang realized that not every factory has the financial prowess to spend tens of thousands of dollars on digitization.
New-age careers like cloud reliability engineer, Artificicial Intelligence (AI) architect, malware analyst, digital transformation specialists and many others have taken the job market by storm. These choices have been fuelled by tech courses like Data Science, DevOps, Cloud Computing, AI and and Machine Learning, Cybersecurity resulting in a huge demand for online certifications from ed-tech platforms who have collaborated with distinguished educational institutions. But is this change here to stay and what is its impact? The online education market is expected to touch Rs 360 billion by 2024, up from Rs 39 billion, according to a recent report by data firm'Research and Markets.' With a futuristic approach, DevOps as a system encompasses everything from organization to culture, processes, and tools and its adoption is growing rapidly.
Deploying machine learning is a multi-step process. Deploying machine learning is a multi-step process. It involves selecting a model, training it for a specific task, validating it with test data, and then deploying and monitoring the model in production. Here, we'll discuss these steps and break them down to introduce you to machine learning. Machine learning refers to systems that, without explicit instruction, are capable of learning and improving.
A research collaboration between China and the UK has devised a new method to reshape faces in video. The technique allows for convincing broadening and narrowing of facial structure, with high consistency and an absence of artifacts. From a YouTube video used as source material by the researchers, actress Jennifer Lawrence appears as a more gaunt personality (right). See the accompanying video embedded at the bottom of the article for many more examples at better resolution. This kind of transformation is usually only possible through traditional CGI methods that would need to entirely recreate the face via detailed and expensive motion-capping, rigging and texturing procedures. Instead, what CGI there is in the technique is integrated into a neural pipeline as parametric 3D face information that's subsequently used as a basis for a machine learning workflow.
Previous studies in medical imaging have shown disparate abilities of artificial intelligence (AI) to detect a person's race, yet there is no known correlation for race on medical imaging that would be obvious to human experts when interpreting the images. We aimed to conduct a comprehensive evaluation of the ability of AI to recognise a patient's racial identity from medical images. Using private (Emory CXR, Emory Chest CT, Emory Cervical Spine, and Emory Mammogram) and public (MIMIC-CXR, CheXpert, National Lung Cancer Screening Trial, RSNA Pulmonary Embolism CT, and Digital Hand Atlas) datasets, we evaluated, first, performance quantification of deep learning models in detecting race from medical images, including the ability of these models to generalise to external environments and across multiple imaging modalities. Second, we assessed possible confounding of anatomic and phenotypic population features by assessing the ability of these hypothesised confounders to detect race in isolation using regression models, and by re-evaluating the deep learning models by testing them on datasets stratified by these hypothesised confounding variables. Last, by exploring the effect of image corruptions on model performance, we investigated the underlying mechanism by which AI models can recognise race.
HSBC's Akash Gupta has won over 45 machine learning hackathons to date. The MachineHack Grandmaster has come second thrice in a row and is currently ranked sixth on the platform. "I've always been fascinated by numbers and patterns. I got very curious about algorithms – how they are made, how they work, and what we can do with them– after I took Andrew Ng's machine learning course," said Akash Gupta. The data scientist spoke about his MachineHack journey in an exclusive interview with Analytics India Magazine.
He leads the team of applications, data, and AI experts ensuring they are developing market-leading solutions and supporting customer teams with the technology and solutions customers need most. Vishal was previously with DXC Technology where he was the senior business leader for their Data & Analytics AI, Machine Learning, and IoT business. Leading a significant pivot in the company's strategy, he leveraged best-in-class partnerships with cloud-based next-gen platforms to implement scalable industrialized solutions for DXC customers. Vishal is a senior executive with experience in multiple geographies including Asia Pacific, India, and the Americas. He has deep experience in consulting across IT and Business Process Services with exposure to Product Management, Design Thinking, Marketing, Operations, and P&L leadership in diverse industries.