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The official Jupyter Conference
Aug 21-22, 2018: Training
Aug 22-24, 2018: Tutorials & Conference
New York, NY

In-Person Training
Hands-on data science with Python

Zachary Glassman (The Data Incubator)
Tuesday, August 21 & Wednesday, August 22
9:00am - 5:00pm
Enterprise and organizational adoption, Extensions and customization, Usage and application
 2-Day Training Location: Concourse B Level: Intermediate
Average rating: ****.
(4.50, 2 ratings)

Participants should plan to attend training courses on both Tuesday and Wednesday. To attend, you must register for a Platinum pass; does not include access to tutorials on Wednesday.

Zachary Glassman leads a hands-on dive into building intelligent business applications using machine learning, walking you through all the steps of developing a machine learning pipeline. You'll explore data cleaning, feature engineering, model building and evaluation, and deployment and extend these models into two applications using real-world datasets.

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

  • Understand fundamental machine learning tools and toolkits
  • Learn how to apply them to two real world data problems

This training is for you because...

  • You're in a data-driven role.

Prerequisites:

  • A basic understanding of Python
  • Familiarity with the Python scientific stack (pandas, NumPy, etc.)

Zachary Glassman leads a hands-on dive into building intelligent business applications using machine learning, walking you through all the steps of developing a machine learning pipeline. You’ll explore data cleaning, feature engineering, model building and evaluation, and deployment and extend these models into two applications using real-world datasets.

Outline

Day 1: Recommendation engine

  • Overview of data and its wrangling
  • Item-item correlations and finding similar items
  • User similarity and predicting user ratings
  • Collaborative filtering
  • Evaluating model performance

Day 2: Anomaly detection

  • Data format and goal
  • Limitations of time series data
  • Detrending and seasonality
  • Windowing and local scores
  • Setting thresholds for classification
  • Online learning

About your instructor

Photo of Zachary Glassman

Zachary Glassman is a data scientist in residence at the Data Incubator. Zachary has a passion for building data tools and teaching others to use Python. He studied physics and mathematics as an undergraduate at Pomona College and holds a master’s degree in atomic physics from the University of Maryland.

Conference registration

Get the Platinum pass or the Training pass to add this course to your package.

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Comments

Picture of Zachary Glassman
Zachary Glassman | DATA SCIENTIST IN RESIDENCE
04/13/2018 2:19pm EDT

Hi Rohan,
The machine learning will be targeted at beginners and we will focus on recommendation systems and anomaly detection. In the process we will learn about scikit-learn and basic supervised ML. This course is different than Machine Learning with TensorFlow because we will not be covering neural networks or graph computation.

Rohan Bareja |
04/13/2018 1:34pm EDT

Hi Zachary, I am interested in this workshop,and wanted to know if you would be teaching machine learning methods specifically for beginners ?

Also, will it be just focused on recommendation systems/anomaly detection ?

How this course is different from Machine Learning with TensorFlow(apart from the obvious different types of ML methods)?