Lynn Langit
Cloud Architect who codes
Cloud Practices for
Machine Learning
@LynnLangit
August 2020
Topics
- 0% Data & Questions
- 20% Dev & Cloud
- 40% Start with Hello (ML)
- 60% Data Samples & Security
- 80% Model Quality
- 100% Scale & Reproduce
Solve for What?
# A hybrid quantum-classical model.
model = tf.keras.Sequential([
# Quantum circuit data comes in inside of tensors.
tf.keras.Input(shape=(), dtype=tf.dtypes.string),
# Parametrized Quantum Circuit (PQC) provides output
# data from the input circuits run on a quantum computer.
tfq.layers.PQC(my_circuit, [cirq.Z(q1), cirq.X(q0)]),
# Output data from quantum computer passed through model.
tf.keras.layers.Dense(50)
])Data
- What - type(s)
- Where - source locations
- When - frequency
- How much -> CLOUD-scale
Get Sample Data
- File Type
- Format
- Quality
- Quantity
Get Cloud Open Data
Dev Environment
The cloud is your laptop, really.
Dev Environment
- Set up a Virtual Machine Image
- Use a Jupyter Notebook
- Use a ML Docker Container Image
Which Cloud?
Vendor/Location
Get Started
- Vendor
- Account Type
- Data Center
Do the Basics
- Account
- Billing
- Security
Hello
ML Cloud
World
Types of Cloud Machine Learning
- Virtual Machines w/your model
- Docker containers w/your (vendor) model
- Vendor APIs
Build vs Buy - AWS
Build vs Buy - GCP
Learn the Cloud ML Services
- SaaS
- PaaS
- IaaS
Hello ML Algorithm w/mnist
- Works?
- Verified?
- Time/Cost?
- Reuse?
- Bias?
Your
Data
Matters
Bias in the Training Data
Model
Quality
Matters
MyCloudML - Example
- Why the cloud? - data volume
- How long will it take? cost?
- What to do first? - ????
Hello MyML
- Works?
- Verified?
- Time/Cost?
- Reuse?
- Bias?
Tools for Fairness - TensorFlow
Cost-effective Scaling
Scaling / Reproducibility
- Works?
- Verified?
- Time/Cost?
- Reuse?
- Bias?
One-page Diagram
MLDevOps - AWS
- Config as Code
- Automated Tests
- Deployment Templates
- CI/CD
Full MLDevOps - AWS
MLDevOps by Example
Domain-specific cloud ML - Bioinformatics
Cloud Practices for
Machine Learning
@LynnLangit
August 2020
Cloud for Machine Learning
By Lynn Langit
Cloud for Machine Learning
Resources and patterns for implementing effective machine learning workloads on the public cloud.
