MLOps with Data Version Control: Tracking & Logging Deep Learning Models
MLOps 2023
| Intermediate
- 12 videos | 1h 30m 50s
- Includes Assessment
- Earns a Badge
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
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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
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2mIn this video, we will discover the key concepts covered in this course. FREE ACCESS
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8m 18sDuring 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
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3. Configuring Cloud Remotes on Data Version Control (DVC)7m 29sFind out how to connect to an S3 bucket from DVC. FREE ACCESS
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4. Visualizing and Tracking the CIFAR 10 Dataset7m 53sIn this video, discover how to visualize and track image data. FREE ACCESS
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5. Tracking Sample Images with DVC5m 27sLearn how to log images for image classification. FREE ACCESS
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6. Setting up the CNN for Image Classification7m 50sIn this video, find out how to set up a convolutional neural network (CNN) for image classification. FREE ACCESS
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7. Tracking PyTorch Lightning Model Training7m 35sDiscover how to track a PyTorch Lightning model during training. FREE ACCESS
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8. Improving Image Classification10m 56sLearn how to improve the image classification model. FREE ACCESS
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9. Configuring Azure Cloud Storage as DVC Remote12m 55sDuring this video, discover how to set up Azure Cloud Storage as a DVC remote. FREE ACCESS
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10. Training and Logging TensorFlow Models9m 23sIn this video, find out how to train and log TensorFlow models. FREE ACCESS
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11. Tracking TensorFlow Models Using DVC8m 47sDuring this video, you will learn how to track TensorFlow models in DVC. FREE ACCESS
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12. Course Summary2m 18sIn this video, we will summarize the key concepts covered in this course. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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