Machine Learning, Deep Learning development in production was still broken. ZenML, an extensible, open-source MLOps framework for production-ready ML pipelines.Read the full...
TensorFlow
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How young and women developers are nurturing the tech ecosystem for a stronger post-COVID-19 world
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It is an important time for developers in Southeast Asia. There are approximately 1.5 million developers in the region, and in the last decade, we’ve seen tremendous technological growth. 2020 has marked the biggest shift yet, as the e-Conomy SEA 2020 report from Google, Temasek and Bain &...
— All the images (plots) are generated and modified by the Author.Read the full...
🤷🏻 The ProblemRead the full...
JavaScript and Python are now the most popular programming languages used on GitHub followed by Java and TypeScript.Read...
At its annual re:Invent developer conference, AWS today announced the launch of AWS Trainium, the company’s next-gen custom chip dedicated to training machine learning models. The company promises that it can offer higher performance than any of its competitors in the cloud, with support for...
Google released a new version of its TensorFlow framework that's optimized for MacBooks running macOS Big Sur.Read...
Learn how cutting-edge computer architecture can unlock new AI capabilities, from common use cases to real-world case studies and more.Read...
In case you missed it, I built a neural network to predict loan risk using a public dataset from LendingClub. Then I built a public API to serve the model’s predictions. That’s nice and all, but… how good is my model?Read the full...
Data Science Libraries that will shine this year.Read the full...
A Step-by-Step Guide (With a Healthy Dose of Data Cleaning)Read the full...
Machine learning groups form Consortium for Python Data API Standards to reduce fragmentation
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Groups like Open Neural Network Exchange launched the Python Data API Standards to make interoperability easier for data scientists and ML practitioners.Read...
Google has adopted an OpenCL-based inference backened for TensorFlow on mobile devices, which the company claims delivers a significant speedup.Read...
Google researchers developed a tool, TF-Coder, that automates the process of developing AI and machine learning models in TensorFlow.Read...
This is part 2 of the two-part article on deploying ML models on mobile. We saw how to convert our ML models to TfLite format here. For those of you who came here first, I recommend you click on the above link to get the whole picture. If you just want the android part ,the demo app we are...
tl;dr - Link to code: TensorFlow GAN model.So the other day I was talking to my rubber ducky about how G-Board predicts my next word, even when those words are entirely made up by me, in that how it actually learns on-device. How amazingly Netflix, Amazon, Google Maps make use of machine learning...
Google's new toolkit introduces a privacy-preserving technique and test for machine learning modules developed in TensorFlow.Read...
Efficient Model Training in the Cloud with Kubernetes, TensorFlow, and Alluxio Open Source
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This article presents the collaboration of Alibaba, Alluxio, and Nanjing University in tackling the problem of Deep Learning model training in the cloud. Various performance bottlenecks are analyzed with detailed optimizations of each component in the architecture. This content was previously...
Uber open-sourced Neuropod, an abstraction layer designed to unify disparate AI frameworks like Google's TensorFlow and Facebook's PyTorch.Read...
Google open-sourced TFRT, a faster and more efficient runtime that'll eventually replace the default runtime in the company's TensorFlow framework.Read...
Deep learning is a subpart of machine learning and artificial intelligence which is also known as deep neural network this networks capable of learning unsupervised from provided data which is unorganized or unlabeled. today, we will implement a neural network in 6 easy steps using TensorFlow to...
In a whitepaper, Google describes DynamicEmbedding, a framework that extends its TensorFlow machine learning framework to 'colossal-scale' applications.Read...
Google's TensorFlow Lite model maker tool adapts state-of-the-art machine learning models for on-device applications, chiefly NLP and computer vision.Read...
Google's new Quantization Aware Training API supports the development of smaller, faster models that don't compromise on accuracy.Read...
INTRODUCTIONRead the full...
Thinking of Machine Learning, the first frameworks that come to mind are Tensorflow and PyTorch, which are currently the state-of-the-art frameworks if you want to work with Deep Neural Networks. Technology is changing rapidly and more flexibility is needed, so Google researchers are developing a...
Google launches TensorFlow Quantum, a machine learning framework for training quantum models
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Google today unveilved TensorFlow Quantum for training hybrid quantum-classical algorithms by combining TensorFlow with open-source quantum library Cirq.Read...