MLOps with Data Version Control: Tracking & Logging Deep Learning Models

MLOps 2023    |    Intermediate
  • 12 videos | 1h 30m 50s
  • Includes Assessment
  • Earns a Badge
Rating 5.0 of 2 users Rating 5.0 of 2 users (2)
Data Version Control (DVC) offers robust support for deep learning models by effectively managing large model files and their dependencies, allowing versioned tracking of complex architectures. This ensures reproducibility in training, evaluation, and deployment pipelines, even in deep learning projects. In this course, you will discover how to track deep learning models through DVC. Using PyTorch Lightning, you will construct a convolutional neural network (CNN) for image classification. Then you will use DVCLive to log and visualize sample images and use the DVCLiveLogger to monitor model metrics in real time via Iterative Studio. Next, you will undertake deep learning model training with TensorFlow. You will set up a CNN for image classification and train your model while leveraging DVCLive to record and display training-related metrics. Finally, you will use the DVCLiveCallback to dynamically visualize metrics during training. This course will equip you with the expertise to effectively build and track deep learning models within DVC's ecosystem.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Set up an aws identity and access management (iam) user and simple storage service (s3) bucket
    Connect to an s3 bucket from dvc
    Visualize and track image data
    Log images for image classification
    Set up a convolutional neural network (cnn) for image classification
  • Track a pytorch lightning model during training
    Improve the image classification model
    Set up azure cloud storage as a dvc remote
    Train and log tensorflow models
    Track tensorflow models in dvc
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 2m
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 8m 18s
    During this video, you will learn how to set up an AWS Identity and Access Management (IAM) user and Simple Storage Service (S3) bucket. FREE ACCESS
  • Locked
    3.  Configuring Cloud Remotes on Data Version Control (DVC)
    7m 29s
    Find out how to connect to an S3 bucket from DVC. FREE ACCESS
  • Locked
    4.  Visualizing and Tracking the CIFAR 10 Dataset
    7m 53s
    In this video, discover how to visualize and track image data. FREE ACCESS
  • Locked
    5.  Tracking Sample Images with DVC
    5m 27s
    Learn how to log images for image classification. FREE ACCESS
  • Locked
    6.  Setting up the CNN for Image Classification
    7m 50s
    In this video, find out how to set up a convolutional neural network (CNN) for image classification. FREE ACCESS
  • Locked
    7.  Tracking PyTorch Lightning Model Training
    7m 35s
    Discover how to track a PyTorch Lightning model during training. FREE ACCESS
  • Locked
    8.  Improving Image Classification
    10m 56s
    Learn how to improve the image classification model. FREE ACCESS
  • Locked
    9.  Configuring Azure Cloud Storage as DVC Remote
    12m 55s
    During this video, discover how to set up Azure Cloud Storage as a DVC remote. FREE ACCESS
  • Locked
    10.  Training and Logging TensorFlow Models
    9m 23s
    In this video, find out how to train and log TensorFlow models. FREE ACCESS
  • Locked
    11.  Tracking TensorFlow Models Using DVC
    8m 47s
    During this video, you will learn how to track TensorFlow models in DVC. FREE ACCESS
  • Locked
    12.  Course Summary
    2m 18s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.

Digital badges are yours to keep, forever.

YOU MIGHT ALSO LIKE

Course Cloud Computing and MLOps: Introduction to MLOps
Rating 4.4 of 17 users Rating 4.4 of 17 users (17)
Course Getting Started with MLOps
Rating 5.0 of 1 users Rating 5.0 of 1 users (1)
Book MLOps Engineering at Scale