Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA

In-Person Training
Forecasting Financial Time Series with Deep Learning on Azure

Francesca Lazzeri (Microsoft)

Participants should plan to attend both days of this 2-day training course. To attend training courses, you must register for a Platinum or Training pass; does not include access to tutorials on Tuesday.

Francesca Lazzeri will walk you through the core steps for using Azure Machine Learning services to train your machine learning models both locally and on remote compute resources.

What you'll learn, and how you can apply it

  • Set up your development environment
  • Access and examine the data
  • Train long short-term memory (LSTM) networks to generate stock market predictions
  • Review training results and register the best model
  • Set up your testing environment
  • Retrieve the model from your workspace
  • Test the model locally
  • Deploy the model
  • Test the deployed model

This training is for you because...

You are a data scientist, software developer, data engineer, or financial data analyst, who wants to use Azure platform and Azure Machine Learning services for machine learning and building financial time series forecasts.


  • Experience coding in Python o A basic understanding of machine learning and deep learning topics and terminology
  • Familiarity with Time Series Forecast (useful but not required)

Hardware and/or installation requirements:

  • A laptop with an up-to-date version of Edge or Chrome.
  • If you don’t have an Azure subscription, create a free account.

Francesca Lazzeri will walk you through the core steps for using Azure Machine Learning services to
train your machine learning models both locally and on remote compute resources. You will use the
training and deployment workflow for Azure Machine Learning service in a Python Jupyter
notebook. You can then use the notebook as a template to train your own machine learning model
with your own data.

Specifically, this tutorial will show how to generate stock market predictions with long short-term
memory (LSTM) networks: LSTM models can use the history of a sequence of data and correctly
predict what the future elements of the sequence are going to be. This is very helpful in many
different financial use cases, for example, when you need to model stock prices correctly.
Finally, you will learn how to deploy the model as a web service in Azure Container Instances (ACI). A
web service is an image, in this case a Docker image, that encapsulates the scoring logic and the
model itself. Each topic will include a lecture combined with hands-on exercises.


  1. Introduction to Time Series Forecast
  2. Introduction to Neural Networks for Time Series Forecast
  3. Azure Machine Learning Services
  4. Applied Use Case: Stock Market Predictions with LSTMs

About your instructor

Photo of Francesca Lazzeri

Francesca Lazzeri is an AI and machine learning scientist on the cloud developer advocacy team at Microsoft. Francesca has multiple years of experience as data scientist and data-driven business strategy expert; she is passionate about innovations in big data technologies and the applications of machine learning-based solutions to real-world problems. Her work on these issues covers a wide range of industries, including energy, oil and gas, retail, aerospace, healthcare, and professional services. Previously, she was a research fellow in business economics at Harvard Business School, where she performed statistical and econometric analysis within the Technology and Operations Management Unit and worked on multiple patent data-driven projects to investigate and measure the impact of external knowledge networks on companies’ competitiveness and innovation. Francesca is a mentor for PhD and postdoc students at the Massachusetts Institute of Technology and enjoys speaking at academic and industry conferences to share her knowledge and passion for AI, machine learning, and coding. Francesca holds a PhD in innovation management.

Twitter for frlazzeri

Conference registration

Get the Platinum pass or the Training pass to add this course to your package. Best Price ends January 11.

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