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این صفحه به‌وسیله ‏Cloud Translation API‏ ترجمه شده است.

بیاموزید که چگونه TensorFlow مشکلات واقعی و روزمره یادگیری ماشین را حل می کند

بررسی کنید که چگونه شرکت های مختلف از صنایع مختلف، ML را برای حل بزرگترین مشکلات خود پیاده سازی می کنند. از مراقبت های بهداشتی گرفته تا شبکه های اجتماعی و حتی تجارت الکترونیک ، ML می تواند در صنعت و شرکت شما ادغام شود.

Airbnb با استفاده از TensorFlow برای طبقه بندی تصاویر و تشخیص اشیا در مقیاس، تجربه مهمان را بهبود می بخشد.

تیم مهندسی و علم داده Airbnb از یادگیری ماشینی با استفاده از TensorFlow برای طبقه‌بندی تصاویر و تشخیص اشیا در مقیاس استفاده می‌کند و به بهبود تجربه مهمان کمک می‌کند.

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TFX

ایرباس از TensorFlow برای استخراج اطلاعات از تصاویر ماهواره‌ای خود و ارائه بینش‌های ارزشمند به مشتریان استفاده می‌کند

ML به نظارت بر تغییرات سطح زمین برای برنامه ریزی شهری، مبارزه با ساخت و سازهای غیرقانونی و نقشه برداری از آسیب ها و تغییرات منظر ناشی از بلایای طبیعی کمک می کند.

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TensorFlow Lite

لایه انتزاعی سخت افزاری Arm به افزایش بیش از 4 برابری عملکرد TensorFlow Lite منجر می شود.

Arm NN for Android Neural Networks API (NNAPI) یک لایه انتزاعی سخت افزاری (HAL) ارائه می دهد که پردازنده های گرافیکی Arm Mali را هدف قرار می دهد و منجر به افزایش عملکرد بیش از 4 برابری چارچوب های یادگیری ماشین مانند TensorFlow Lite می شود.

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Carousell از TensorFlow برای بهبود تجربه خریدار و فروشنده استفاده می کند

Carousell با استفاده از TensorFlow در Google Cloud ML، مدل‌های یادگیری ماشینی را با تصویر عمیق و درک زبان طبیعی می‌سازد. فروشندگان از یک تجربه پست ساده با تشخیص تصویر بهره می برند و خریداران لیست های مرتبط بیشتری را از طریق توصیه ها و جستجوی تصویر کشف می کنند.

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TensorFlow Lite

CEVA شبکه های آموزش دیده TensorFlow را در پردازنده های Deep Learning خود تبدیل می کند

پردازنده‌های هوش مصنوعی NeuPro و CEVA-XM CEVA برای یادگیری عمیق و استنتاج هوش مصنوعی در لبه به‌طور خودکار شبکه‌های آموزش‌دیده TensorFlow را برای استفاده در دستگاه‌های جاسازی‌شده بلادرنگ با استفاده از کامپایلر CEVA CDNN تبدیل می‌کنند.

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China Mobile از TensorFlow برای بهبود میزان موفقیت خود در قطع عناصر شبکه استفاده می کند

China Mobile یک سیستم یادگیری عمیق با استفاده از TensorFlow ایجاد کرده است که می تواند به طور خودکار پنجره زمان قطع را پیش بینی کند، گزارش عملیات را تأیید کند و ناهنجاری های شبکه را تشخیص دهد. این قبلاً با موفقیت از بزرگترین جابجایی صدها میلیون شماره IoT HSS در جهان پشتیبانی کرده است.

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TensorFlow گواهی خرید تلفن همراه در کوکاکولا را امکان پذیر می کند

پیشرفت در هوش مصنوعی و بلوغ TensorFlow شرکت کوکاکولا را قادر ساخت تا به یک قابلیت اثبات خرید بدون اصطکاک برای برنامه وفاداری خود دست یابد.

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جنرال الکتریک یک شبکه عصبی را با استفاده از TensorFlow برای شناسایی آناتومی MRI مغز آموزش داد

با استفاده از TensorFlow، GE Healthcare در حال آموزش یک شبکه عصبی برای شناسایی آناتومی خاص در طول آزمایشات تصویربرداری رزونانس مغناطیسی مغز (MRI) است تا به بهبود سرعت و قابلیت اطمینان کمک کند.

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TensorFlow Lite

گوگل TensorFlow را ساخته است تا یادگیری ماشینی را برای همه به ارمغان بیاورد

Google از TensorFlow برای تقویت پیاده‌سازی ML در محصولاتی مانند Search، Gmail و Translate استفاده می‌کند تا به محققان در اکتشافات جدید کمک کند، و حتی پیشرفت‌هایی در چالش‌های بشردوستانه و زیست‌محیطی ایجاد کند.

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TensorFlow.js

InSpace از TensorFlow.js برای فیلترهای سمیت بلادرنگ در چت آنلاین استفاده می کند

InSpace از TensorFlow.js استفاده می کند تا نظرات سمی را قبل از ارسال حتی با انجام تمام سمت کلاینت استنتاج در مرورگر شناسایی کند و نیاز به ارسال متن به سرور شخص ثالث برای طبقه بندی را از بین ببرد.

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اینتل عملکرد استنتاج TensorFlow را در پردازنده Xeon® Scalable بهینه می کند

همکاری اینتل با Google منجر به بهبود عملکرد استنتاج تا 2.8 برابر در مدل‌های مختلف شده است تا به نفع طیف وسیعی از مشتریانی باشد که TensorFlow را بر روی پلتفرم‌های اینتل اجرا می‌کنند.

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TFX

Kakao از TensorFlow برای پیش‌بینی میزان تکمیل درخواست‌های ride-hailing استفاده می‌کند

Kakao Mobility از TensorFlow و TensorFlow Serving برای پیش‌بینی احتمال نرخ‌های کامل سفر زمانی که رانندگان برای انجام درخواست‌های سواری اعزام می‌شوند، استفاده می‌کند.

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Lenovo Intelligent Computing Orchestration از TensorFlow برای کمک به تسریع انقلاب هوشمند استفاده می کند.

پلتفرم Lenovo LiCO به آموزش هوش مصنوعی و محاسبات با کارایی بالا سنتی سرعت می بخشد و آموزش یادگیری عمیق را با ادغام و بهینه سازی TensorFlow بهینه می کند. LiCO مدل های مختلف تنسورفلو داخلی را ارائه می دهد و از آموزش توزیع شده بهینه این مدل ها پشتیبانی می کند.

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Liulishuo از TensorFlow برای کمک به آموزش زبان های جدید استفاده می کند

تیم الگوریتم Liulishuo اولین بار TensorFlow را در پروژه یادگیری ماشین داخلی خود در اوایل سال 2016 اعمال کرد. این چارچوب یادگیری ماشینی با استفاده آسان به تیم کمک کرد تا برنامه ای برای آموزش زبان انگلیسی بسازند.

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TensorFlow.js

Modiface از TensorFlow.js در تولید برای آرایش AR در مرورگر استفاده کرد

ModiFace از مدل TensorFlow.js FaceMesh برای شناسایی ویژگی‌های کلیدی صورت و ترکیب آن‌ها با سایه‌زنان WebGL استفاده می‌کند و به کاربران این امکان را می‌دهد تا با حفظ حریم خصوصی، آرایش دیجیتالی محصولات برند L'Oreal را امتحان کنند. تجربه زنده به طور کامل در مرورگر اجرا می شود، بنابراین هیچ داده ای از کاربر برای پردازش به سرور ارسال نمی شود.

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طبقه‌بندی خودکار دسته‌های محصولات خرید NAVER با استفاده از TensorFlow

استفاده از TensorFlow NAVER Shopping به طور خودکار بیش از 20 میلیون محصول تازه ثبت نام شده را در روز با حدود 5000 دسته مطابقت می دهد تا محصولات را به طور سیستماتیک سازماندهی کند و امکان جستجوی آسان تر را برای کاربران فراهم کند.

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NERSC یک برنامه علمی DL را با استفاده از TensorFlow به 27000 پردازنده گرافیکی Nvidia V100 Tensor Core تبدیل کرد.

NERSC و NVIDIA موفق شدند یک برنامه یادگیری عمیق علمی را به 27000 پردازنده گرافیکی Nvidia V100 Tensor Core تبدیل کنند و در این فرآیند مانع ExaFLOP را بشکنند.

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TFX

OpenX ترافیک را برای درخواست های حجم بالا با استفاده از TFX اولویت بندی می کند

OpenX TFX و Google Cloud Platform را در تبادل تبلیغات خود ادغام می کند تا بیش از یک میلیون درخواست را در هر ثانیه پردازش کند و پاسخ ها را در کمتر از 15 میلی ثانیه ارائه دهد.

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پی پال از TensorFlow برای ماندن در لبه برش تشخیص تقلب استفاده می کند

PayPal با استفاده از TensorFlow، یادگیری انتقال عمیق و مدل‌سازی مولد، توانسته است الگوهای کلاهبرداری پیچیده زمانی متفاوت را تشخیص دهد تا دقت کاهش تقلب را افزایش دهد و در عین حال تجربه کاربران قانونی را از طریق افزایش دقت در شناسایی بهبود بخشد.

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TensorFlow Lite

کوالکام مدل‌های TensorFlow را در پلتفرم‌های موبایل اسنپدراگون و فراتر از آن سرعت می‌بخشد

Qualcomm مدل‌های TensorFlow و TensorFlow Lite را در پلتفرم‌های موبایل اسنپدراگون و در مجموعه‌های تراشه‌های طراحی‌شده برای اینترنت اشیا، محاسبات، XR و خودروسازی بهینه‌سازی و سرعت می‌بخشد.

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تشخیص بیماری در تصاویر OCT شبکیه با TensorFlow

طبقه بندی بیماری و تقسیم بندی بر روی تصاویر OCT شبکیه با استفاده از TensorFlow انجام شد. سه نوع بیماری به عنوان نئوواسکولاریزاسیون مشیمیه، زگیل زجاجیه یا ادم شبکیه دیابتی طبقه بندی شدند. پس از تقسیم بندی، Sinovation Ventures مرز ضایعات مشکوک را در تصویربرداری ارائه کرد.

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TFX

Spotify توصیه هایی را برای کاربران با TFX شخصی می کند

Spotify از خطوط لوله TFX و Kubeflow در جاده هموار خود برای سیستم‌های ML استفاده می‌کند، مجموعه‌ای از محصولات و پیکربندی‌ها برای استقرار یک راه‌حل یادگیری ماشینی سرتاسر که هدف آن تیم‌هایی است که سفرهای ML خود را شروع می‌کنند.

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Swisscom عملیات پشتیبانی مشتری را با مدل سفارشی TensorFlow بهینه می کند

Swisscom از ظرفیت TensorFlow برای مدل‌های یادگیری ماشینی عمیقا سفارشی‌سازی شده برای طبقه‌بندی متن و تعیین هدف مشتریان خود پس از دریافت درخواست‌هایشان استفاده می‌کند.

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TensorFlow Lite

Texas Instruments Processor SDK TensorFlow Lite را برای استنتاج یادگیری ماشین در لبه ادغام می کند.

پردازنده SDK مدل‌های TensorFlow Lite را بهینه می‌کند، استنتاج CNN/DNN را از هسته‌های Arm® محاسباتی عمومی به شتاب‌دهنده‌های سخت‌افزاری هدفمند می‌آورد، که قابلیت‌های یادگیری ماشین را در بینایی ماشین، روباتیک، ADAS خودرو و بسیاری از برنامه‌های کاربردی دیگر افزایش می‌دهد.

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TFX

رتبه بندی توییت ها با TensorFlow

توییتر از TensorFlow برای ساخت «خط زمانی رتبه‌بندی‌شده» خود استفاده کرد و به کاربران این امکان را داد که مطمئن شوند مهم‌ترین توییت‌های خود را حتی اگر هزاران کاربر را دنبال می‌کنند، از دست ندهند.

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TensorFlow Lite

پیشنهاد از پیش تنظیمات برای تصاویر: ساخت "برای این عکس" در VSCO

VSCO از TensorFlow Lite برای توسعه ویژگی «برای این عکس» استفاده کرد، که از یادگیری ماشینی روی دستگاه برای شناسایی نوع عکسی که شخص در حال ویرایش است استفاده می‌کند و سپس تنظیمات پیش‌فرض مربوطه را از فهرست انتخاب‌شده پیشنهاد می‌کند.

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TensorFlow Lite

WPS Office: یک دفتر هوشمند مبتنی بر TensorFlow

WPS Office چندین سناریو تجاری مانند تشخیص تصویر روی دستگاه و OCR تصویر بر اساس TensorFlow را پیاده سازی می کند.

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بیاموزید که چگونه TensorFlow مشکلات واقعی و روزمره یادگیری ماشین را حل می کند

با TensorFlow به راحتی بسازید، مستقر کنید و آزمایش کنید