Deployment of Mahine Learning Models

Deployment Of Machine Learning Models In Production | Python  eBooks & eLearning

Posted by Sigha at April 3, 2023
Deployment Of Machine Learning Models In Production | Python

Deployment Of Machine Learning Models In Production | Python
Last updated 4/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 5.16 GB | Duration: 9h 39m

Deploy ML Model with BERT, DistilBERT, FastText NLP Models in Production with Flask, uWSGI, and NGINX at AWS EC2

2024 Deployment of Machine Learning Models in Production  eBooks & eLearning

Posted by lucky_aut at Jan. 25, 2024
2024 Deployment of Machine Learning Models in Production

2024 Deployment of Machine Learning Models in Production
Last updated 1/2024
Duration: 9h40m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 5.29 GB
Genre: eLearning | Language: English

Deploy ML Model with BERT, DistilBERT, FastText NLP Models in Production with Flask, uWSGI, and NGINX at AWS EC2

Deployment of Machine Learning Models  eBooks & eLearning

Posted by ELK1nG at May 26, 2021
Deployment of Machine Learning Models

Deployment of Machine Learning Models
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.42 GB | Duration: 9h 36m

Learn how to integrate robust and reliable Machine Learning Pipelines in Production

Deployment of Machine Learning Models  eBooks & eLearning

Posted by lucky_aut at Aug. 5, 2023
Deployment of Machine Learning Models

Deployment of Machine Learning Models
Last updated 2/2023
Duration: 10h 27m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 5.06 GB
Genre: eLearning | Language: English

Learn how to integrate robust and reliable Machine Learning Pipelines in Production

Deployment of Machine Learning Models (updated 4/2022)  eBooks & eLearning

Posted by ELK1nG at May 14, 2022
Deployment of Machine Learning Models (updated 4/2022)

Deployment of Machine Learning Models (updated 4/2022)
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.45 GB | Duration: 10h 22m

Learn how to integrate robust and reliable Machine Learning Pipelines in Production
Machine Learning Engineering with Python: Manage the production life cycle of machine learning models

Machine Learning Engineering with Python
by Andrew P. McMahon

English | 2021 | ISBN: ‎ 1801079250 | 277 pages | True (PDF EPUB) | 32.14 MB

Machine Learning in Trading: Step by step implementation of Machine Learning models  eBooks & eLearning

Posted by Free butterfly at May 17, 2023
Machine Learning in Trading: Step by step implementation of Machine Learning models

Machine Learning in Trading: Step by step implementation of Machine Learning models by QuantInsti Quantitative Learning, Ishan Shah, Rekhit Pachanekar
English | 2021 | ISBN: N/A | ASIN: B09HKHPT9M | 240 pages | EPUB | 2.57 Mb
Machine Learning Engineering with Python: Manage the production life cycle of machine learning models using MLOps (repost)

Machine Learning Engineering with Python:
Manage the production life cycle of machine learning models using MLOps with practical examples

English | 2021 | ISBN: ‎ 1801079250 | 276 Pages | PDF EPUB (True) | 30 MB

Create And Deploy Deep Learning Project Web Apps  eBooks & eLearning

Posted by lucky_aut at March 19, 2021
Create And Deploy Deep Learning Project Web Apps

Create And Deploy Deep Learning Project Web Apps
Duration: 2h 45m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 1.19 GB
Genre: eLearning | Language: English

Learn deployment of machine learning and deep learning projects with python on heruko
Building Scalable Deep Learning Pipelines on AWS: Develop, Train, and Deploy Deep Learning Models

Building Scalable Deep Learning Pipelines on AWS: Develop, Train, and Deploy Deep Learning Models
English | 2024 | ASIN : B0DG4N89W1 | 749 Pages | True PDF,EPUB | 6.98 MB

This book is your comprehensive guide to creating powerful, end-to-end deep learning workflows on Amazon Web Services (AWS). The book explores how to integrate essential big data tools and technologies―such as PySpark, PyTorch, TensorFlow, Airflow, EC2, and S3―to streamline the development, training, and deployment of deep learning models.