#cuml результаты поиска
Everything you need to know about @rapidsai, #BlazingSQL, @Graphistry, #cuDF, #cuML, #cuDNN, #cuGRAPH, #ETL, #MachineLearning, #DeepLearning, #Scaling and our #Benchmarks in one awesome poster. Check it out!
Good show tonight at F&F in 'sauga! Thx again @DJjustMARVELOUS for the spot & #CUML #CanUMakeEmLaugh #SickKids shirt...
Collab between @nvidia & @Snowflake - modeling and genomics in Snowflake Notebooks leveraging #cuDF & #cuML for , boosting efficiency for computationally demanding tasks.
Your scikit-learn and pandas workflows can now easily scale up and run on GPUs in Snowflake! We are excited to announce that Snowflake ML now comes preinstalled with @nvidia's cuML and cuDF libraries, delivering native GPU acceleration for popular data science tools like…
@becker_data and @dante_dgd wrote a great blog post of using @rapidsai #cuML and @scikit_learn to dramatically improve the perf of running ensemble models. We made minor changes to get it to run on app.blazingsql.com Check it out! gist.github.com/roaramburu/9b4… #GPU #DataScience
Building #ML models too slow? Check out the latest blog series by @tomekdrabas from @blazingsql on how to accelerate #GPU Machine Learning with @RAPIDSai #cuML from @NVIDIAAI: nvda.ws/3cVIDfp
Au colloque dédié au gd juriste av @olivierrichefou président @lamayenne fac de droit qui a 40ans ajd #Droit #CUML
The secret to @rapidsai is the @ApacheArrow in-memory GPU DataFrame. With a common data format we can pass data between jobs with just a device pointer. This lets #BlazingdSQL #cuDF #cuML #cuDNN etc.. integrate without incurring serialization and deserialization costs!
Enhanced UMAP Performance on GPUs with RAPIDS cuML: RAPIDS cuML introduces a faster, scalable UMAP implementation using GPU acceleration, addressing challenges in large dataset processing with new algorithms for… dlvr.it/TFxtVm #UMAP #RAPIDS #cuML #GPU #acceleration
Working on a new demo showing the seamless handoff between #BlazingSQL and #cuML. It all works on the #GPU DataFrame #GDF so it's seamless. ML ready in 5 lines of code. Stay tuned. @rapidsai @gpuoai #MachineLearning #ETL #BigData #RAPIDSAI
Built to scale, @RAPIDSai 0.9 is here! #cuDF: more robust, up to 10x faster; #cuGraph: PageRank 300GB in 30 secs; #cuML: multi-node kmeans/random forest & the new Forest Inference Library that accelerates @XGBoostProject/ #LightGBM inference over 30x! nvda.ws/30GPnq2
先ほど #PyConJP にて『TensorFlow/RAPIDSを使用した機械学習ハンズオン』を行いました。.@rapidsai のウェブサイト "TRY NOW IN COLAB" より、NVIDIAのT4上でRAPIDSを無料で試せるGoogle Colabにアクセス可能です。本日紹介したRAPIDSの #cuDF および #cuML をぜひお試しください！ #datascience
People who say that Python is slow have never seen it fly on a GPU! 🐍 #cuml #cudf #pandas #scikitlearn
Hear what @MariyaSha888 from Python Simplified has to say about #GTC25 and GPU acceleration of #Python using cuML.
RAPIDS Up to .11 medium.com/rapids-ai/rapi… #cuml
medium.com
RAPIDS Up to .11
As 2019 comes to a close, the RAPIDS team couldn’t end the year without one last release.
Collab between @nvidia & @Snowflake - modeling and genomics in Snowflake Notebooks leveraging #cuDF & #cuML for , boosting efficiency for computationally demanding tasks.
Your scikit-learn and pandas workflows can now easily scale up and run on GPUs in Snowflake! We are excited to announce that Snowflake ML now comes preinstalled with @nvidia's cuML and cuDF libraries, delivering native GPU acceleration for popular data science tools like…
7/20Use Rapids ecosystem for data science at scale. cuDF (pandas on GPU), cuML (scikit-learn on GPU), cuGraph for network analysis. Game-changer for big data processing. #Rapids #cuDF #cuML #DataScience #BigData
🚀🚀Boost Scikit-Learn with GPU Power! Unlock up to 50x performance gains with NVIDIA's cuML, integrating GPU acceleration into scikit-learn. Train models in seconds, not hours! #GPU #ScikitLearn #cuML #MachineLearning
cuML: Your ML Models Deserve a GPU Upgrade! cuML leverages NVIDIA GPUs for insane speedups! Handle millions of rows without breaking a sweat Supports SVMs, DBSCAN, UMAP & more Why crawl when you can fly? ✈️ #cuML #MachineLearning #RAPIDS #GPUPower #artificial_intelligence
People who say that Python is slow have never seen it fly on a GPU! 🐍 #cuml #cudf #pandas #scikitlearn
Hear what @MariyaSha888 from Python Simplified has to say about #GTC25 and GPU acceleration of #Python using cuML.
cuML: Machine Learning at GPU Speed! Like scikit-learn, but on steroids (NVIDIA GPUs) Runs ML models 10-100x faster than CPUs Supports Regression, KNN, PCA, K-Means & more Perfect for BIG data & real-time AI Ditch the CPU. Go GPU! #cuML #MachineLearning #RAPIDS…
Enhanced UMAP Performance on GPUs with RAPIDS cuML: RAPIDS cuML introduces a faster, scalable UMAP implementation using GPU acceleration, addressing challenges in large dataset processing with new algorithms for… dlvr.it/TFxtVm #UMAP #RAPIDS #cuML #GPU #acceleration
#xgboost #cuml #kaggle mi última configuracion de los hiperparametros en xgbregressor me ha producido este rendimiento en jpx competition, estoy que flipo porque es la primera vez en que un modelo mío tiene tanta precisión basado enteramente en la feature engineering pública. 💪🏾
@BoozAllen + @nvidia = Best Paper (of 5) @MLSysConf #MLSys Its a general framework for distance functions that results in fast sparse GPU kernels! You've probably been benefiting for months if you use #cuml @RAPIDSai @cjnolet @BradReesWork @divyegala @32Eaton @zstats @oatesbag
I’m happy to announce the pre-print for our new paper “Semiring Primitives for Sparse Neighborhood Methods on the GPU.” We show that semirings can enable many important neighborhood machine learning methods and provide a novel implementation on the GPU. arxiv.org/pdf/2104.06357…
Did I just do a Jacobi singular value decomp of a 3.1 million row/300 column matrix within seconds? #cuda #cuML #linearalgebra #gpu
Everything you need to know about @rapidsai, #BlazingSQL, @Graphistry, #cuDF, #cuML, #cuDNN, #cuGRAPH, #ETL, #MachineLearning, #DeepLearning, #Scaling and our #Benchmarks in one awesome poster. Check it out!
Building #ML models too slow? Check out the latest blog series by @tomekdrabas from @blazingsql on how to accelerate #GPU Machine Learning with @RAPIDSai #cuML from @NVIDIAAI: nvda.ws/3cVIDfp
Good show tonight at F&F in 'sauga! Thx again @DJjustMARVELOUS for the spot & #CUML #CanUMakeEmLaugh #SickKids shirt...
The secret to @rapidsai is the @ApacheArrow in-memory GPU DataFrame. With a common data format we can pass data between jobs with just a device pointer. This lets #BlazingdSQL #cuDF #cuML #cuDNN etc.. integrate without incurring serialization and deserialization costs!
Working on a new demo showing the seamless handoff between #BlazingSQL and #cuML. It all works on the #GPU DataFrame #GDF so it's seamless. ML ready in 5 lines of code. Stay tuned. @rapidsai @gpuoai #MachineLearning #ETL #BigData #RAPIDSAI
Au colloque dédié au gd juriste av @olivierrichefou président @lamayenne fac de droit qui a 40ans ajd #Droit #CUML
Enhanced UMAP Performance on GPUs with RAPIDS cuML: RAPIDS cuML introduces a faster, scalable UMAP implementation using GPU acceleration, addressing challenges in large dataset processing with new algorithms for… dlvr.it/TFxtVm #UMAP #RAPIDS #cuML #GPU #acceleration
🚀🚀Boost Scikit-Learn with GPU Power! Unlock up to 50x performance gains with NVIDIA's cuML, integrating GPU acceleration into scikit-learn. Train models in seconds, not hours! #GPU #ScikitLearn #cuML #MachineLearning
#xgboost #cuml #kaggle mi última configuracion de los hiperparametros en xgbregressor me ha producido este rendimiento en jpx competition, estoy que flipo porque es la primera vez en que un modelo mío tiene tanta precisión basado enteramente en la feature engineering pública. 💪🏾
Built to scale, @RAPIDSai 0.9 is here! #cuDF: more robust, up to 10x faster; #cuGraph: PageRank 300GB in 30 secs; #cuML: multi-node kmeans/random forest & the new Forest Inference Library that accelerates @XGBoostProject/ #LightGBM inference over 30x! nvda.ws/30GPnq2
Announcing @rapidsai 0.8! Highlights: #cuDF+@PyTorch 10X speedup, #cuML adds RF, #cuGraph gets 3X faster with more algos. The community is growing. Check out RAPIDS. Get a @nvidia #GPU, #conda install, and enjoy some summer of coding fun! nvda.ws/2JEZqWs
Learn how the new open source Forest Inference Library (FIL) in RAPIDS #cuML 0.9 eliminates bottlenecks by accelerating GBDT and RF inference with #GPUs. nvda.ws/2NSiMK7
Something went wrong.
Something went wrong.
United States Trends
- 1. Cowboys 71.1K posts
- 2. LeBron 94.9K posts
- 3. Gibbs 19K posts
- 4. Lions 87.4K posts
- 5. Pickens 13.3K posts
- 6. #OnePride 10K posts
- 7. Brandon Aubrey 7,024 posts
- 8. Ferguson 10.5K posts
- 9. #DALvsDET 6,104 posts
- 10. Eberflus 2,438 posts
- 11. Goff 8,450 posts
- 12. CeeDee 10.2K posts
- 13. Shang Tsung 21.2K posts
- 14. Bland 8,446 posts
- 15. scott hunter 2,721 posts
- 16. DJ Reed N/A
- 17. Al Michaels N/A
- 18. Schotty 1,806 posts
- 19. fnaf 2 24K posts
- 20. Paramount 18K posts