Develop an End-to-End Machine Learning Model

This interactive two-hour live online course is designed to take participants on a deep dive into the topic of training, tuning, evaluating, and selecting an ML model. Topics covered include business understanding for ML solution development, exploratory data analysis (EDA), model development, hyperparameter optimization, and considerations for MLOps. Jupyter Notebook exercises in Python will be integrated throughout the course.

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

By the end of this hands-on course, you’ll understand:

• The phases of the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework.
• Exploratory Data Analysis (EDA) and data preparation/transformation.
• Stages in developing and evaluating an ML model.
• Long-term considerations for model maintenance (MLOps).

And you’ll be able to:

• Use the CRISP-DM framework for developing ML solutions.
• Frame a business problem as a data problem.
• Evaluate the quality of training data and how to prepare it for modeling.

This training is for you because…

• You’re an aspiring analyst, software developer/engineer interested in learning about ML.
• You work with data and understand the basics of Python coding.
• You want to become a data scientist and/or ML/MLOps engineer.

Prerequisites

• Basic understanding of math, statistics and probability
• Ability to understand mathematical notation
• Experience programming in Python

Jupyter Notebooks / Setup 

• Get set up with Anaconda Notebooks. Watch this video to learn how. 
• Or, if you prefer to use a Jupyter Notebook on your machine, you can install Anaconda Distribution (free) and open JupyterLab. Instructions can be found within the Get Started with Anaconda course or in our online documentation. 
• Alternatively, you can use any preferred Jupyter Notebook service.

Recommended preparation

• Introduction to Python Programming on-demand course
• Introduction to Machine Learning on-demand course

About the Instructor

John Sukup is Principal Consultant at Expected X, a data strategy and MLOps solutions consultancy providing clients with detailed, graduated approaches to realizing the full potential of working with data. His experience working with data spans 16 years from consumer market research, to data science, to machine learning engineering. He has acted as the lead professional trainer for machine learning and related topics at Cisco Systems and has been featured in Forbes, Oracle, and Data Science Central.

Expected X

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Cost: $49. Anaconda Learning subscription is not required.

You may cancel your registration at any time before the course airs. Once the course is live, there are no refunds or credits. All registered users will receive a Zoom recording of the live course one day after the course airs.

Important info:

The tutorial will be conducted using Zoom Meetings. It is important that the name you used to register for the event is the same as the name you use when you login to Zoom. If this will not be the case, please email learning@anaconda.com to let us know.

All participants will have their microphones muted and cameras off upon entry to help minimize distractions during the live event. Support and Q&A will be conducted via the Chat function within Zoom.

Questions? Issues? Contact learning@anaconda.com.