Machine learning and data science are growing in popularity, especially since machine learning algorithms were demonstrated to be able to make better predictions than human experts in some cases. Even if you have no experience with machine learning or artificial intelligence, it's likely that you've heard of both concepts before, even if you don't know exactly what they are or how they work. Machine learning allows computers to make accurate predictions based on previous data and experience, similar to the way humans learn new things and form memories. Not sure where to start? Let this guide help you find the best machine learning platforms on the market today!

STR's Analytics division researches and develops advanced analytics and machine learning-based solutions to solve challenging problems related to national security. Our team consists of passionate and motivated engineers with advanced degrees in engineering, computer science, mathematics, and data sciences, who are seeking opportunities to use their deep technical knowledge and creativity to tackle some of the hardest problems that our customers face. Our projects span multiple different data modalities and incorporate advanced algorithms, deep learning, and statistical techniques to uncover patterns in social media, structured and unstructured text, time series, geospatial, and imagery data, and must operate under challenging constraints not typically found in the commercial world. The tools and technologies we develop have real world impact and are used by analysts to extract and enrich intelligence information around the globe. In the Machine Learning Engineer – Algorithms Lead role, you will lead teams that develop and evaluate statistical and machine learning algorithms to uncover hidden information and patterns from a diverse collection of massive datasets.

The particle swarm optimization (PSO) algorithm is a population-based search algorithm based on the simulation of the social behavior of birds within a flock. The initial intent of the particle swarm concept was to graphically simulate the graceful and unpredictable choreography of a bird flock, to discover patterns that govern the ability of birds to fly synchronously, and to suddenly change direction by regrouping in an optimal formation. From this initial objective, the concept evolved into a simple and efficient optimization algorithm. So, just like the Genetic Algorithm, PSO is inspired by nature. In PSO, individuals, also referred to as particles, are "flown" through hyperdimensional search space. Changes to the position of particles within the search space are based on the social-psychological tendency of individuals to emulate the success of other individuals.

Here at Hugging Face, we're on a journey to advance good Machine Learning and make it more accessible. Along the way, we contribute to the development of technology for the better. We have built the fastest-growing, open-source, library of pre-trained models in the world. With over 100M installs and 65K stars on GitHub, over 10 thousand companies are using HF technology in production, including leading AI organizations such as Google, Elastic, Salesforce, Algolia, and Grammarly. As an ML engineer in vision, you will work mainly into existing open-source libraries, such as Transformers and Datasets to boost the support for vision or multi-modal models and datasets.

Diagnosis is crucial to providing efficacious healthcare. Let's have a look at the history. Hippocrates (400 BCE) was the first to systemize the process of diagnosis based on a person's symptoms and medical history. About 2500 years later in 1895 the X-ray was discovered by Konrad Roentgen. With this invention, we could now watch radiation pass through the body, leaving shadows of the solid objects.

Each day, the lives of more than 2 billion people across the globe are impacted by chronic diseases. Moreover, the economic burden on society of treating chronic disease is spinning out of control. Today, this dire situation appears unlikely to change as 95% of global healthcare costs are spent on treating rather than preventing chronic diseases. FL84, Inc. is a privately held early-stage company that is applying advanced biological and computational platforms to discover breakthroughs in detection of and intervention against the etiologies that drive progression from health to disease. Our goal is to leverage our proprietary platforms to disrupt the current approach of treating chronic disease too late.

The field of computer vision has rapidly evolved in recent years and achieved results that seemed like science fiction a few years back. These breakthroughs have many causes -- building better, more accessible compute resources, but also the fact that they are the closest thing we have to Open Source Data Science (OSDS). Revealing the source code to the community unlocks the "wisdom of the crowd" and enables innovation and problem-solving at scale. One of the most popular OS projects in computer vision is YOLO (You Only Look Once). YOLO is an efficient real-time object detection algorithm, first described in the seminal 2015 paper by Joseph Redmon et al.

Tech giant MetaAhas created a single artificial intelligence (AI)-based model capable of translating across 200 different languages, including many not supported by current commercial tools. According to The Verge, the company is open-sourcing the project in the hopes that others will build on its work. The AI model is part of an ambitious R&D project by Meta to create a so-called "universal speech translator," which the company sees as important for growth across its many platforms -- from Facebook and Instagram to developing domains like VR and AR. Machine translation not only allows Meta to better understand its users (and so improve the advertising systems that generate 97 per cent of its revenue) but could also be the foundation of a killer app for future projects like its augmented reality glasses. Experts in machine translation told the website that Meta's latest research was ambitious and thorough, but noted that the quality of some of the model's translations would likely be well below that of better-supported languages like Italian or German.

Blockmate Ventures inc ("Blockmate" or the "Company") announces that its subsidiary Hivello has entered into a partnership with Web3 infrastructure company DLTx to expand the Hivello network of Internet of Things (IoT) hotspots. Based in Oslo and publicly listed on the Oslo Stock Exchange, DLTx specializes in protocols that provide predictable value both in utility and economics with a strong track record in identifying growth opportunities in the Web3 space. This includes their involvement in Bitcoin mining for many years as an early investor in one of the largest industrial scale Bitcoin mining operations in North America. By partnering with DLTx, Hivello will secure access to DLTx's suppliers, financiers, and management expertise which have been at the forefront of developing and launching 10 of the most important protocols in the blockchain space, including Ethereum. Hivello will issue equity to DLTx which will receive a 40% stake in Hivello while Blockmate retains the remaining 60%.

Level 5 autonomous vehicles (AVs) will allow shipping companies to significantly decrease their costs and their liability as they will no longer need long-haul truck drivers. However, this also applies to smugglers. Trafficking of drugs, people, weapons, and black market goods will all receive a boon from AVs. There will be a massive increase in vehicles on the road with the advent of fully-autonomous technology. Long-haul delivery vehicles could largely become operated with no passengers inside, and will likely not even have a place for a passenger.