Name: Production-Ready Applied Deep Learning: Learn how to construct and deploy complex models in PyTorch and TensorFlow deep learning frameworks
Brand: Packt Publishing Limited
SKU: 329290080
Price: 89.97 AUD
Availability: InStock

Table of Contents

Effective Planning of Deep Learning-Driven Projects

Data Preparation for Deep Learning Projects

Developing a Powerful Deep Learning Model

Experiment Tracking, Model Management, and Dataset Versioning

Data Preparation in the Cloud

Efficient Model Training

Revealing the Secret of Deep Learning Models

Simplifying Deep Learning Model Deployment

Scaling a Deep Learning Pipeline

Improving Inference Efficiency

Deep Learning on Mobile Devices

Monitoring Deep Learning Endpoints in Production

Reviewing the Completed Deep Learning Project

About the Author

Tomasz Palczewski is currently working as a staff software engineer at Samsung Research America. He has a Ph.D. in physics and an eMBA degree from Quantic. His zeal for getting insights out of large datasets using cutting-edge techniques led him to work across the globe at CERN (Switzerland), LBNL (Italy), J-PARC (Japan), University of Alabama (US), and University of California (US). In 2016, he was deployed to the South Pole to calibrate the world's largest neutrino telescope. Later, he decided to pivot his career and focus on applying his skills in industry. Currently, he works on modeling user behavior and creating value for advertising and marketing verticals by deploying machine learning (ML), deep learning, and statistical models at scale. Jaejun (Brandon) Lee is currently working as an AI research lead at RoboEye.ai, integrating cutting-edge algorithms in computer vision and AI into industrial automation solutions. He obtained his master’s degree from the University of Waterloo with research focused on natural language processing (NLP), specifically speech recognition. He has spent many years developing a fully productionized yet open source wake word detection toolkit with a web browser deployment target, Howl. Luckily, his effort has been picked up by Mozilla's Firefox Voice and it is actively providing a completely hands-free experience to many users all over the world. Lenin Mookiah is a machine learning engineer who has worked with reputed tech companies – Samsung Research America, eBay Inc., and Adobe R&D. He has worked in the technology industry for over 11 years in various domains: banking, retail, eDiscovery, and media. He has played various roles in the end-to-end productization of large-scale machine learning systems. He mainly employs the big data ecosystem to build reliable feature pipelines that data scientists consume. Apart from his industrial experience, he researched anomaly detection in his Ph.D. at Tennessee Tech University (US) using a novel graph-based approach. He studied entity resolution on social networks during his master’s at Tsinghua University, China.

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