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Learn how TensorFlow solves real, everyday machine learning problems

Explore how various companies from a wide variety of industries implement ML to solve their biggest problems. From healthcare to social networks and even ecommerce, ML can be integrated into your industry and company.

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All case studies and mentions

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Airbnb improves the guest experience by using TensorFlow to classify images and detect objects at scale

The Airbnb engineering and data science team applies machine learning using TensorFlow to classify images and detect objects at scale, helping to improve the guest experience.

Airbus is using TensorFlow to extract information from their satellite images and deliver valuable insights to their clients

ML helps with monitoring changes to the Earth's surface for urban planning, fighting illegal construction and mapping damage and landscape changes caused by natural catastrophes.

Arm's Hardware Abstraction Layer leads to a more than 4x performance boost to TensorFlow Lite

Arm NN for Android Neural Networks API (NNAPI) provides a Hardware Abstraction Layer (HAL) that targets Arm Mali GPUs and leads to more than a 4x performance boost to machine learning frameworks such as TensorFlow Lite.

Carousell uses TensorFlow to improve the buyer and seller experience

Carousell builds machine learning models with deep image and natural language understanding using TensorFlow on Google Cloud ML. Sellers benefit from a simplified posting experience with image recognition, and buyers discover more relevant listings through recommendations and image search.

CEVA converts TensorFlow trained networks in their Deep Learning processors

CEVA’s NeuPro and CEVA-XM AI processors for Deep Learning and AI inferencing at the edge automatically convert TensorFlow trained networks for use in real-time embedded devices using the CEVA CDNN Compiler.

China Mobile is using TensorFlow to improve their success rate of network element cutovers

China Mobile has created a deep learning system using TensorFlow that can automatically predict cutover time window, verify operation logs, and detect network anomalies. This has already successfully supported the world’s largest relocation of hundreds of millions IoT HSS numbers.

How machine learning with TensorFlow enabled mobile proof-of-purchase at Coca-Cola

Advances in artificial intelligence and the maturity of TensorFlow enabled the Coca-Cola Company to finally achieve a long-sought frictionless proof-of-purchase capability.

GE trained a neural network using TensorFlow to identify anatomy on MRIs of the brain

Using Tensorflow, GE Healthcare is training a neural network to identify specific anatomy during brain magnetic resonance imaging (MRI) exams to help improve speed and reliability.

Google built TensorFlow to bring machine learning to everyone

Google uses TensorFlow to power ML implementations in products like Search, Gmail, and Translate, to aid researchers in new discoveries, and even to forge advances in humanitarian and environmental challenges.

Intel has partnered with Google to optimize TensorFlow inference performance across different models.

This work has resulted in up to 2.8x performance improvement which benefits the TensorFlow community and a wide range of customers using TensorFlow on Intel platforms

Kakao uses TensorFlow to predict the completion rate of ride-hailing requests

Kakao Mobility uses TensorFlow & TensorFlow Serving to predict the probability of trip completed rate when we dispatch drivers to fulfill ride hailing requests.

Lenovo Intelligent Computing Orchestration is using TensorFlow to help accelerate the intelligent revolution

The Lenovo LiCO platform accelerates AI training and traditional High Performance Computing, and optimizes deep learning training with TensorFlow integration and optimization. LiCO provides various built-in TensorFlow models and supports optimized distributed training of these models.

Liulishuo uses TensorFlow to help teach new languages

The Liulishuo algorithm team first applied TensorFlow to its internal machine learning project in early 2016. This easy-to-use machine learning framework helped the team build an application to teach English.

Auto-classification of NAVER Shopping Product Categories using TensorFlow

Using TensorFlow NAVER Shopping automatically matches over 20 million newly registered products a day to around 5,000 categories in order to organize products systematically and allow easier searching for users.

How NERSC scaled a scientific DL application to 27,000+ Nvidia V100 Tensor Core GPUs using TensorFlow

NERSC and NVIDIA succeeded at scaling a scientific Deep Learning application to 27,000+ Nvidia V100 Tensor Core GPUs, breaking the ExaFLOP barrier in the process.

PayPal is using TensorFlow to stay at the cutting edge of Fraud Detection

Using TensorFlow, deep transfer learning and generative modeling, PayPal has been able to recognize complex temporally varying fraud patterns to increase fraud decline accuracy while improving experience of legitimate users through increased precision in identification.

Qualcomm accelerates TensorFlow models on Snapdragon mobile platforms and beyond

Qualcomm optimizes and accelerates TensorFlow and TensorFlow Lite models on Snapdragon mobile platforms, and across chipset portfolios designed for IoT, compute, XR and automotive.

Detecting disease on OCT images of the retina with TensorFlow

Disease classification and segmentation were performed on retinal OCT images using TensorFlow. The three disease types were classified as either choroidal neovascularization, vitreous warts or diabetic retinal edema. After segmentation, Sinovation Ventures provided the boundary of the suspected lesions in the imaging.

How Swisscom’s custom-built TensorFlow model improved business operations by classifying text

Swisscom leverages TensorFlow's capacity to deeply customize machine learning models to classify text and determine the intent of their customers upon receiving their calls.

Texas Instruments Processor SDK integrates TensorFlow Lite for machine learning inference at the edge

Processor SDK optimizes TensorFlow Lite models, offloading CNN/DNN inference from general compute Arm® cores to purpose built hardware accelerators, which enhances machine learning capabilities in machine vision, robotics, automotive ADAS and many other applications.

Ranking tweets with TensorFlow

Twitter used TensorFlow to build their "Ranked Timeline," allowing users to ensure that they don't miss their most important tweets even if they follow thousands of users.

Suggesting Presets for Images: Building “For This Photo” at VSCO

VSCO used TensorFlow Lite to develop the “For This Photo” feature, which uses on-device machine learning to identify what kind of photo someone is editing and then suggest relevant presets from a curated list.

WPS Office: an intelligent office based on TensorFlow

WPS Office implements multiple business scenarios, such as on-device image recognition and image OCR based on TensorFlow.