Learn how SUMPRODUCT function works in Google Sheets

Learn how SUMPRODUCT function works. See how to use SUMPRODUCT function to create conditional summing like SUMIF that works with data from other spreadsheets (Google Sheets).

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Google's TPU's being primed for the Quantum Jump

The liquid-cooled Tensor Processing Units, built to slot into server racks, can deliver up to 100 petaflops of compute.

The liquid-cooled Tensor Processing Units, built to slot into server racks, can deliver up to 100 petaflops of compute.

As the world is gearing towards more automation and AI, the need for quantum computing has also grown exponentially. Quantum computing lies at the intersection of quantum physics and high-end computer technology, and in more than one way, hold the key to our AI-driven future.

Quantum computing requires state-of-the-art tools to perform high-end computing. This is where TPUs come in handy. TPUs or Tensor Processing Units are custom-built ASICs (Application Specific Integrated Circuits) to execute machine learning tasks efficiently. TPUs are specific hardware developed by Google for neural network machine learning, specially customised to Google’s Machine Learning software, Tensorflow.

The liquid-cooled Tensor Processing units, built to slot into server racks, can deliver up to 100 petaflops of compute. It powers Google products like Google Search, Gmail, Google Photos and Google Cloud AI APIs.

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Learn how SUMPRODUCT function works in Google Sheets

Learn how SUMPRODUCT function works. See how to use SUMPRODUCT function to create conditional summing like SUMIF that works with data from other spreadsheets (Google Sheets).

Subscribe: https://www.youtube.com/c/LearnGoogleSpreadsheets/featured

#google-sheets #sumproduct

Inside MoveNet, Google’s Latest Pose Detection Model

Ahead of Google I/O, Google Research launched a new pose detection model in TensorFlow.js called MoveNet. This ultra-fast and accurate model can detect 17 key points in the human body. MoveNet is currently available on TF Hub with two variants — Lightning and Thunder.

While Lightning is intended for latency-critical applications, Thunder is for applications that call for higher accuracy. Both models claim to run faster than real-time (30+ frames per second (FPS)) on most personal computers, laptops and phones.

The model can be launched in the browser using TensorFlow.js architecture with no server calls needed after the initial page load or external packages. The live demo version is available here.

Currently, the MoveNet model works for the individual in the camera field-of-view. But, soon, Google Research looks to extend the MoveNet model to the multi-person domain so that developers can support applications with multiple people.

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Google Reveals "What is being Transferred” in Transfer Learning

Recently, researchers from Google proposed the solution of a very fundamental question in the machine learning community — What is being transferred in Transfer Learning? They explained various tools and analyses to address the fundamental question.

The ability to transfer the domain knowledge of one machine in which it is trained on to another where the data is usually scarce is one of the desired capabilities for machines. Researchers around the globe have been using transfer learning in various deep learning applications, including object detection, image classification, medical imaging tasks, among others.

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Top 10 Fun Machine Learning Experiments By Google Released in 2020

Experiments with Google is an exciting website where Google developers, as well as others around the globe, creates intuitive experiments based on machine learning and other techniques. The experiments are the projects that push the boundaries of technology, art, design and more. Currently, the website includes more than 1500 experiments.

Here, we have curated a list of ten such fun machine learning experiments that are released in 2020.

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