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  • MPI Ethno. Forsch.  (2)
  • HU Berlin
  • 2020-2024  (2)
  • 1995-1999
  • Molino, Piero  (2)
  • [Place of publication not identified] : Pragmatic AI Solutions  (2)
  • Internet videos  (2)
Datasource
  • MPI Ethno. Forsch.  (2)
  • HU Berlin
Material
Language
Years
  • 2020-2024  (2)
  • 1995-1999
Year
Publisher
  • [Place of publication not identified] : Pragmatic AI Solutions  (2)
Keywords
  • 1
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (51 min.)) , sound, color.
    DDC: 004.67/82
    Keywords: Cloud computing ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Detailed conversation about Declarative AutoML with Piero Molino author of Ludwig and co-founder Predibase. 00:00 Intro 00:50 First meeting Piero at Strata in Moscone Center 10:50 Why Declarative AutoML? 12:00 Introducing Declarative ML Systems 16:44 Ludwig: declarative ML systems on PyTorch 18:06 Github Statistics for Ludwig 19:51 Ludwig training example via CLI 21:09 pip install ludwig and using the Programmatic API 26:32 How does Ludwig work? 26:53 Training with Ludwig 27:34 Predicting with Ludwig 29:59 Running Experiments with Ludwig 31:04 ludwig experiment --dataset 32:09 Input - Encoder - Decoder - Output 34:15 ParallelCNN encoding 35:42 Pretrained Transformers: bert distilbert t5 roberta gpt-2 40:44 concat combiner 41:18 Number features decoding 41:37 Vector featuers decoding 41:52 Sequence features decoding 42:30 Training parameters: batch_size, epochs, learning_rate, ... 43:07 Preprocessing parameters 43:33 Speaker Verification 44:03 Expected Time of Delivery 44:35 Summarization 45:04 Distributed Training, Ludwig on Ray 45:23 Running Ludwig on Ray 47:18 Ludwig Hyperpot with RayTune (Advanced) 48:51 Ludwig on Kubernetes 49:15 Managed Ludwig in Predibase 49:54 Predibase: Low-code ML, High-Performance.
    Note: Presenters, Noah Gift and Piero Molino. - Online resource; title from title details screen (O'Reilly, viewed June 27, 2022)
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Language: English
    Pages: 1 online resource (1 video file (3 hr., 39 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.3/1
    Keywords: Machine learning ; Cloud computing ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Enterprise MLOps Interviews Learn Enterprise MLOps from the experts This video series interviews the experts at MLOps to learn how to use MLOps to build and deploy ML models. Interviews Include: Introduction GPT-3: O'Reilly authors Shubham Saboo and Sandra Kublik: I talk with the authors of the new O'Reilly book GPT-3 about a range of topics, including why they wrote the book. Conversation with Piero Molino and Ludwig/Predibase: Detailed conversation about Declarative AutoML with Piero Molino, author of Ludwig and co-founder Predibase. Asaf Somekh, CEO Iguazio: Talk at Duke MIDS MLOps Course: Life of a Model (or the brutal reality of applying ML in enterprises and how to deal with it). Javier Luraschi and Pedro Luraschi, Co-Founders of Hal9.ai: Discuss MLOps with Javascript, including no-code and low-code approaches and Tensorflow.js. Topics Covered Include: Enterprise MLOps MLOps MLOps on AWS MLOps on GCP MLOps on Azure MLOps and DevOps MLOps with Ludwig Additional Popular Resources Pytest Master Class AWS Solutions Architect Professional Course Github Actions and GitOps in One Hour Video Course Jenkins CI/CD and Github in One Hour Video Course AWS Certified Cloud Practitioner Video Course Advanced Testing with Pytest Video Course AWS Solutions Architect Certification In ONE HOUR Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers, and Microservices MLOPs Foundations: Chapter 2 Walkthrough of Practical MLOps Learn Docker containers in One Hour Video Course Introduction to MLOps Walkthrough AZ-900 (Azure Fundamentals) Quick reference guide 52 Weeks of AWS Episode 8: Infrastructure as Code with CDK and AWS Lambda Learn GCP Cloud Functions in One Hour Video Course Python Devops in TWO HOURS! MLOps Platforms From Zero: DatMLOps Platforms From Zero: Databricks, MLFlow/MLRun/SKLearn AWS Machine Learning Certification In ONE HOUR Fast, documented Machine Learning APIs with FastAPI Zero to One: AWS Lambda with SAM and Python in One Hour AWS Storage Solutions 2022: EBS/S3/EFS/Glacier Python Bootcamp for Data Testing In Python book Minimal Python book Practical MLOps book Python for DevOps-Playlist.
    Note: Online resource; title from title details screen (O'Reilly, viewed August 9, 2022)
    Library Location Call Number Volume/Issue/Year Availability
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