GTC21
LET'S INVENT THE FUTURE TOGETHER
Join Us at the Conference for AI Innovators, Technologists, and Creatives on April 12 - 16, 2021.
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March 3, 2021
Jetson Project of the Month: OpenDog, a Gesture Controlled Robot
March 3, 2021
The Human Genome Center at University of Tokyo Adopts NVIDIA Clara Parabricks for Rapid Genomic Analysis
March 2, 2021
New Jetson Nano 2GB Developer Kit Grant Program Launches
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January 2021
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Building a Question and Answering Service Using Natural Language Processing with NVIDIA NGC and Google Cloud
NVIDIA GTC provides training, insights, and direct access to experts. Join us for breakthroughs in AI, data center, accelerated computing, healthcare, game development, networking, and more. Invent the future with us: April 12-16, 2021. Enterprises across industries are leveraging natural language process (NLP) solutions—from chatbots to audio transcription—to improve customer engagement, increase employee productivity, and […]
Pandas DataFrame Tutorial – Beginner’s Guide to GPU Accelerated DataFrames in Python
This post is the first installment of the series of introductions to the RAPIDS ecosystem. The series explores and discusses various aspects of RAPIDS that allow its users solve ETL (Extract, Transform, Load) problems, build ML (Machine Learning) and DL (Deep Learning) models, explore expansive graphs, process geospatial, signal, and system log data, or use […]
End-to-End Blueprint for Customer Churn Modeling and Prediction, Part 1
If you want to solve a particular kind of business problem with machine learning, you’ll likely have no trouble finding a tutorial showing you how to extract features and train a model. However, building machine learning systems isn’t just about training models or even about finding the best features; if you want a blueprint for […]
Accelerating Random Forests Up to 45x Using cuML
Random forests are a popular machine learning technique for classification and regression problems. By building multiple independent decision trees, they reduce the problems of overfitting seen with individual trees. In this post, I review the basic random forest algorithms, show how their training can be parallelized on NVIDIA GPUs, and finally present benchmark numbers demonstrating […]
