Open Source frameworks such as TensorFlow, MXNet, or PyTorch enable anyone to model and train Deep Neural Networks. While there are many great tutorials and talks showing us the best ways for training models, there is few information on what happens after we have trained our model? How can we store, utilize, and update it? In this talk, we look at the complete Deep Learning Pipeline and looks at topics such as deployments, multi-tenancy, jupyter notebooks, model serving, and more.
7. 1. Explore data using
Jupyter notebook
2. Train the model
using TensorFlow
3. Monitor training progress
using TensorBoard 4. Debug Model using tfdbg 5. Serve Model using TensorFlow
Serving
8. Cloud Pipeline
2. Explore data using
Jupyter notebook
3. Train the model
using TensorFlow
4. Monitor training progress
using TensorBoard 5. Debug Model using tfdbg 6. Serve Model using TensorFlow
Serving
1. Data Preparation using
Spark
7.Streaming of requests
...
9. Open Source Pipeline
2. Explore data using
Jupyter notebook
3. Train the model
using TensorFlow
4. Monitor training progress
using TensorBoard 5. Debug Model using tfdbg 6. Serve Model using TensorFlow
Serving
1. Data Preparation using
Spark
7. Kafka stream of
requests
Kubeflow
10. Deep Learning Pipeline
Data &
Streaming
Users
Frameworks &
Cluster
Models
Distributed Data
Storage and
Streaming
Model Serving
Data Preparation and
Analysis
Deep Learning Tools
and Distributed
Hosting
Building Machine
Learning Model
Sending Model to
Clients
Monitoring & Operations
12. Data Management
Data &
Streaming
Users
Frameworks &
Cluster
Models
Distributed Data
Storage and
Streaming
Model Serving
Data Preparation and
Analysis
Deep Learning Tools
and Distributed
Hosting
Building Machine
Learning Model
Sending Model to
Clients
Monitoring & Operations
46. Model Management
Data &
Streaming
Users
Frameworks &
Cluster
Models
Distributed Data
Storage and
Streaming
Model Serving
Data Preparation and
Analysis
Deep Learning Tools
and Distributed
Hosting
Building Machine
Learning Model
Sending Model to
Clients
Monitoring & Operations