Zachary Glassman offers a foundation in building intelligent business applications using machine learning, walking you through all the steps of developing a machine learning pipeline, from prototyping to production. You’ll explore data cleaning, feature engineering, model building and evaluation, and deployment and extend these models into two applications using real-world datasets. All work will be done in Python.
Day 1: Anomaly detection
Day 2: Recommendation engine
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.
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Comments
Hi,
This course will be focused on two applications, one an anomaly detection system for time series data and the other a recommendation system. Along the way, we will learn some of the fundamentals of data wrangling and machine learning in Python. This will be a technical course (we will write code!).
Zach
Hi – I’m interested in this course. I’ve just started using machine learning through Python for chemoinformatics applications. Would this course be suitable or is it more focussed on business applications?
Hi Abderrahim,
To prepare ahead of time, please take some time to look over the Python Pandas package. I think you will be able to catch up pretty quickly in the afternoon session.
Zach
Dear Zachary,
Unfortunately I won’t be able to attend class Monday morning due to professional constraints. I will be joining the classe for the afternoon session. Is it possible somehow to catch up on the missing lessons prior to the course ?Thank you !
Hi Daniele,
We will be using scikit-learn for ML and pandas for data manipulation. Aside from that we will be using some other libraries like matplotlib, NumPy, and SciPy.
Dear Zachary,
apart from python and pandas, which are explicitly quoted, may you please elaborate a bit more on the sentence “all work will be done in python”? i.e. which tools are you going to use throughout the training? (e.g. which ML frameworks, etc)
Thanks!