Thu June 21, 2018
Galvanize San Francisco: Naive Bayes Algorithm for Text Classification
SEE EVENT DETAILS
About the Event:
This is an introduction to using Naive Bayes for text classification. We will learn how to code Naive Bayes to classify text documents, such as whether a news article is "sports" or "business". You'll learn how Naive Bayes works, where it can be used, and you'll get a chance to run it on real text data. We’ll be doing hands-on coding in Python. You’ll leave this session equipped to apply this classification technique to other text datasets.
Prerequisites:
This event is intended for beginner to intermediate data science students. People who have done a little machine learning before and want to add Natural Language Processing to their data science toolbox. It does not require in-depth knowledge of statistics or probability. If you have never seen Python before, never fear! Beginners are welcome to come to listen, learn, and observe. If you've already got some familiarity with Python, you’ll get more out the workshop! Participants who are familiar with concepts of data analysis, statistics, and probability will be better equipped to apply their skills after the conclusion of this meetup.
What to Bring:
Bring your laptop and charger. All course materials will be online.
What You’ll Learn:
What is Bayes Theorem and why it's useful
How the Naive Bayes algorithm extends from Bayes Theorem
How to build a Naive Bayes algorithm to classify text
How to evaluate our classifier’s performance
Which resources to continue to develop your skills
Schedule:
6:00 pm – Doors open & Networking
6:30 pm – Lesson Kickoff
6:45 pm – Introduction to machine learning
7:15 pm - Introduction to the Naive Bayes for text classification
8:30 pm – Wrap-Up
Meet Your Instructor:
Dr. Brian Spiering is a Professor of Computer Science at the University of San Francisco and freelance consultant. He teaches humans the languages of computers (primarily Python) and teaches computers the languages of humans (through Natural Language Processing and Artificial Intelligence). He is active in the San Francisco tech community through volunteering and mentoring.
About Galvanize:
Galvanize is the premiere dynamic learning community for technology. With campuses located in booming technology sectors throughout the country, Galvanize provides a community for each the following:
Education - part-time and full-time training in web development, data science, and data engineering
Workspace - whether you’re a freelancer, startup, or established business, we provide beautiful spaces with a community dedicated to support your company’s growth
Networking - events in the tech industry happen constantly in our campuses, ranging from popular Meetups to multi-day international conferences
To learn more about Galvanize, visit galvanize.com or email [email protected].
show less
This is an introduction to using Naive Bayes for text classification. We will learn how to code Naive Bayes to classify text documents, such as whether a news article is "sports" or "business". You'll learn how Naive Bayes works, where it can be used, and you'll get a chance to run it on real text data. We’ll be doing hands-on coding in Python. You’ll leave this session equipped to apply this classification technique to other text datasets.
Prerequisites:
This event is intended for beginner to intermediate data science students. People who have done a little machine learning before and want to add Natural Language Processing to their data science toolbox. It does not require in-depth knowledge of statistics or probability. If you have never seen Python before, never fear! Beginners are welcome to come to listen, learn, and observe. If you've already got some familiarity with Python, you’ll get more out the workshop! Participants who are familiar with concepts of data analysis, statistics, and probability will be better equipped to apply their skills after the conclusion of this meetup.
What to Bring:
Bring your laptop and charger. All course materials will be online.
What You’ll Learn:
What is Bayes Theorem and why it's useful
How the Naive Bayes algorithm extends from Bayes Theorem
How to build a Naive Bayes algorithm to classify text
How to evaluate our classifier’s performance
Which resources to continue to develop your skills
Schedule:
6:00 pm – Doors open & Networking
6:30 pm – Lesson Kickoff
6:45 pm – Introduction to machine learning
7:15 pm - Introduction to the Naive Bayes for text classification
8:30 pm – Wrap-Up
Meet Your Instructor:
Dr. Brian Spiering is a Professor of Computer Science at the University of San Francisco and freelance consultant. He teaches humans the languages of computers (primarily Python) and teaches computers the languages of humans (through Natural Language Processing and Artificial Intelligence). He is active in the San Francisco tech community through volunteering and mentoring.
About Galvanize:
Galvanize is the premiere dynamic learning community for technology. With campuses located in booming technology sectors throughout the country, Galvanize provides a community for each the following:
Education - part-time and full-time training in web development, data science, and data engineering
Workspace - whether you’re a freelancer, startup, or established business, we provide beautiful spaces with a community dedicated to support your company’s growth
Networking - events in the tech industry happen constantly in our campuses, ranging from popular Meetups to multi-day international conferences
To learn more about Galvanize, visit galvanize.com or email [email protected].
About the Event:
This is an introduction to using Naive Bayes for text classification. We will learn how to code Naive Bayes to classify text documents, such as whether a news article is "sports" or "business". You'll learn how Naive Bayes works, where it can be used, and you'll get a chance to run it on real text data. We’ll be doing hands-on coding in Python. You’ll leave this session equipped to apply this classification technique to other text datasets.
Prerequisites:
This event is intended for beginner to intermediate data science students. People who have done a little machine learning before and want to add Natural Language Processing to their data science toolbox. It does not require in-depth knowledge of statistics or probability. If you have never seen Python before, never fear! Beginners are welcome to come to listen, learn, and observe. If you've already got some familiarity with Python, you’ll get more out the workshop! Participants who are familiar with concepts of data analysis, statistics, and probability will be better equipped to apply their skills after the conclusion of this meetup.
What to Bring:
Bring your laptop and charger. All course materials will be online.
What You’ll Learn:
What is Bayes Theorem and why it's useful
How the Naive Bayes algorithm extends from Bayes Theorem
How to build a Naive Bayes algorithm to classify text
How to evaluate our classifier’s performance
Which resources to continue to develop your skills
Schedule:
6:00 pm – Doors open & Networking
6:30 pm – Lesson Kickoff
6:45 pm – Introduction to machine learning
7:15 pm - Introduction to the Naive Bayes for text classification
8:30 pm – Wrap-Up
Meet Your Instructor:
Dr. Brian Spiering is a Professor of Computer Science at the University of San Francisco and freelance consultant. He teaches humans the languages of computers (primarily Python) and teaches computers the languages of humans (through Natural Language Processing and Artificial Intelligence). He is active in the San Francisco tech community through volunteering and mentoring.
About Galvanize:
Galvanize is the premiere dynamic learning community for technology. With campuses located in booming technology sectors throughout the country, Galvanize provides a community for each the following:
Education - part-time and full-time training in web development, data science, and data engineering
Workspace - whether you’re a freelancer, startup, or established business, we provide beautiful spaces with a community dedicated to support your company’s growth
Networking - events in the tech industry happen constantly in our campuses, ranging from popular Meetups to multi-day international conferences
To learn more about Galvanize, visit galvanize.com or email [email protected].
read more
This is an introduction to using Naive Bayes for text classification. We will learn how to code Naive Bayes to classify text documents, such as whether a news article is "sports" or "business". You'll learn how Naive Bayes works, where it can be used, and you'll get a chance to run it on real text data. We’ll be doing hands-on coding in Python. You’ll leave this session equipped to apply this classification technique to other text datasets.
Prerequisites:
This event is intended for beginner to intermediate data science students. People who have done a little machine learning before and want to add Natural Language Processing to their data science toolbox. It does not require in-depth knowledge of statistics or probability. If you have never seen Python before, never fear! Beginners are welcome to come to listen, learn, and observe. If you've already got some familiarity with Python, you’ll get more out the workshop! Participants who are familiar with concepts of data analysis, statistics, and probability will be better equipped to apply their skills after the conclusion of this meetup.
What to Bring:
Bring your laptop and charger. All course materials will be online.
What You’ll Learn:
What is Bayes Theorem and why it's useful
How the Naive Bayes algorithm extends from Bayes Theorem
How to build a Naive Bayes algorithm to classify text
How to evaluate our classifier’s performance
Which resources to continue to develop your skills
Schedule:
6:00 pm – Doors open & Networking
6:30 pm – Lesson Kickoff
6:45 pm – Introduction to machine learning
7:15 pm - Introduction to the Naive Bayes for text classification
8:30 pm – Wrap-Up
Meet Your Instructor:
Dr. Brian Spiering is a Professor of Computer Science at the University of San Francisco and freelance consultant. He teaches humans the languages of computers (primarily Python) and teaches computers the languages of humans (through Natural Language Processing and Artificial Intelligence). He is active in the San Francisco tech community through volunteering and mentoring.
About Galvanize:
Galvanize is the premiere dynamic learning community for technology. With campuses located in booming technology sectors throughout the country, Galvanize provides a community for each the following:
Education - part-time and full-time training in web development, data science, and data engineering
Workspace - whether you’re a freelancer, startup, or established business, we provide beautiful spaces with a community dedicated to support your company’s growth
Networking - events in the tech industry happen constantly in our campuses, ranging from popular Meetups to multi-day international conferences
To learn more about Galvanize, visit galvanize.com or email [email protected].
show less
Date/Times:
44 Tehama Street, San Francisco, CA 94105
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