July usually sees Amazon's incredibly popular Prime Day sales event. While it may be postponed to later on in the year, you can still grab some incredible seasonal discounts in the Amazon Summer Sale. The flash sale, which ends on Sunday 12 July, is a great time to pick up huge bargains across Amazon's departments, including big savings on popular tech items. Today marks the first day of the Amazon Summer Sale and to kick things off the mega-site is slashing the price of the iconic Echo Dot with clock. Knocking a whopping 50 per cent off the full price, it means you can now get the Alexa speaker for only £29.99. But you'll have to be quick as the offer expires at midnight.

Then this course is for you!

The Global Artificial Intelligence (AI) As a Service Market report gives a detailed overview of the key market drivers, restraints, and trends and analyzes …

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As a veteran of way too many zoom conferences, It's perhaps not all that surprising that I would have discovered one of the cooler features of the app - the ability to create an algorithmic green screen that lets you superimpose both static background and videos behind you. The algorithm is not perfect - every so often a shoulder will disappear or hair will suddenly do really weird things, but given that it's basically isolating your outline, ascertaining what's the background and what's you, and then superimposing (or, in the jargon of the SFX industry compositing) the new background over what's left, the effect is pretty damned impressive. There is now a thriving industry of companies that supply specialty green screens that you can set up behind you for a surprisingly inexpensive amount, letting you quite literally put yourself in the middle of the action. For remote roleplaying, especially as the dungeon master, it's hard to beat, but it's also an indication of just how rapidly we are reaching the point where what had once been studio-level graphical effects are now making their way to our desktops. In a previous article, I made the observation that there is typically a gap of about six years between the time that your favorite special effects first appear in Hollywood (or more properly, in the area around Skywalker ranch south of San Jose that's become the mecca of the digital effects industry) and the time that the same special effects make their way to high-end gaming systems.

CyberCoders seeks a Data Scientist – Machine Learning, Building Information to develop algorithms for building information, facility operations and …

This team would include data scientists to build the machine-learning tool, data engineers to structure and clean the data, and an agile coach to …

… market with an augmented interpretation of radiographs using artificial intelligence and machine learning. This new approach to veterinary radiology …

Radio Frequency powered Cognitive Radio Networks (RF-CRN) are likely to be the eyes and ears of upcoming modern networks such as Internet of Things (IoT), requiring increased decentralization and autonomous operation. To be considered autonomous, the RF-powered network entities need to make decisions locally to maximize the network throughput under the uncertainty of any network environment. However, in complex and large-scale networks, the state and action spaces are usually large, and existing Tabular Reinforcement Learning technique is unable to find the optimal state-action policy quickly. In this paper, deep reinforcement learning is proposed to overcome the mentioned shortcomings and allow a wireless gateway to derive an optimal policy to maximize network throughput. When benchmarked against advanced DQN techniques, our proposed DQN configuration offers performance speedup of up to 1.8x with good overall performance.

Clustering can be used to extract insights from data or to verify some of the assumptions held by the domain experts, namely data segmentation. In the literature, few methods can be applied in clustering qualitative values using the context associated with other variables present in the data, without losing interpretability. Moreover, the metrics for calculating dissimilarity between qualitative values often scale poorly for high dimensional mixed datasets. In this study, we propose a novel method for clustering qualitative values, based on Hierarchical Clustering (HQC), and using Maximum Mean Discrepancy. HQC maintains the original interpretability of the qualitative information present in the dataset. We apply HQC to two datasets. Using a mixed dataset provided by Spotify, we showcase how our method can be used for clustering music artists based on the quantitative features of thousands of songs. In addition, using financial features of companies, we cluster company industries, and discuss the implications in investment portfolios diversification.