What we're about

We are a group of techies and community members interested in open government and civic hacking. We host hack nights, workshops, and talks plus work with the municipal government to provide open datasets. We are a Code for America Brigade in Princeton and are organizing Princeton's third civic hackathon as part of National Day of Civic Hacking. If you're a techie, work in local government, or are a community member interested in civic engagement, this group is for you!

Check out our website http://codeforprinceton.org and like us on facebook https://www.facebook.com/codeforprinceton and follow us on twitter https://twitter.com/codeprinceton

Note: By coming to Code for Princeton events, you agree to allow Code for Princeton to use your photo on its social media platforms and press.

Upcoming events (5)

AI: (NLP) Capstone

Needs a location

Learn about artificial intelligence and machine learning, through this course series. Each of the two monthly module can be taken independently of each other, but we do ask that attendees try to attend each of the four classes within the module. If you cannot attend one of classes, arrangements can be made with the instructor, to catch up. Only basic python knowledge is required to attend these classes. Participants must know how to call a function, and loop. Instructors: Vinicius Pantoja and Kashiap Murali, Princeton School of AI Natural Language Processing (NLP) (March) - The first module is to create a solution using a very prominent sub-field of AI called Natural Language Processing(NLP). In this course you will learn how to capture the their sentiment and main characteristics of client reviews regarding a certain product by learning how to grab text, clean it, extract the main words and sentences, and analyze the sentiment. Part 1: Business overview and Basic Implementation (tokenization & word cloud) Wednesday March 6, 6-8pm Part 2: PoS tagging/tagging texts/NER/Sentiment Analysis Wednesday March 13, 6-8pm Part 3: Recommendation System NLP Tuesday March 19, 6-8pm Part 4: Capstone Wednesday March 27, 6-7pm

AI: (CV) Business Overview and Basic Implementation

Needs a location

Learn about artificial intelligence and machine learning, through this course series. Each of the two monthly module can be taken independently of each other, but we do ask that attendees try to attend each of the four classes within the module. If you cannot attend one of classes, arrangements can be made with the instructor, to catch up. Only basic python knowledge is required to attend these classes. Participants must know how to call a function, and loop. Instructors: Vinicius Pantoja and Kashiap Murali, Princeton School of AI Computer Vision (April) - This module will focus on a field where there has been loads of recent developments, Computer Vision (CV). Self driving cars, object detection, flower classification, etc. all fall into this wide and interesting bucket. You will learn how to analyze an image and classify it into different categories by capturing the image, preprocessing the image, and finally, building a model that is trained on these images and can classify new ones. We will also briefly explore the cyber security risks associated with Computer Vision and discuss industry trends. Part 1: Business Overview and Basic Implementation Wednesday April 3, 6-8pm Part 2: Convolutional Neural Networks 1 (identifying objects) Wednesday April 10, 6-8pm Part 3: Convolutional Neural Networks 2 Wednesday April 17, 6-8pm Part 4: Capstone Wednesday April 24, 6-7pm

AI : (CV) Convolutional Neural Networks 1 (identifying objects)

Princeton Public Library

Learn about artificial intelligence and machine learning, through this course series. Each of the two monthly module can be taken independently of each other, but we do ask that attendees try to attend each of the four classes within the module. If you cannot attend one of classes, arrangements can be made with the instructor, to catch up. Only basic python knowledge is required to attend these classes. Participants must know how to call a function, and loop. Instructors: Vinicius Pantoja and Kashiap Murali, Princeton School of AI Computer Vision (April) - This module will focus on a field where there has been loads of recent developments, Computer Vision (CV). Self driving cars, object detection, flower classification, etc. all fall into this wide and interesting bucket. You will learn how to analyze an image and classify it into different categories by capturing the image, preprocessing the image, and finally, building a model that is trained on these images and can classify new ones. We will also briefly explore the cyber security risks associated with Computer Vision and discuss industry trends. Part 1: Business Overview and Basic Implementation Wednesday April 3, 6-8pm Part 2: Convolutional Neural Networks 1 (identifying objects) Wednesday April 10, 6-8pm Part 3: Convolutional Neural Networks 2 Wednesday April 17, 6-8pm Part 4: Capstone Wednesday April 24, 6-7pm

AI : (CV) Convolutional Neural Networks 2

Princeton Public Library

Learn about artificial intelligence and machine learning, through this course series. Each of the two monthly module can be taken independently of each other, but we do ask that attendees try to attend each of the four classes within the module. If you cannot attend one of classes, arrangements can be made with the instructor, to catch up. Only basic python knowledge is required to attend these classes. Participants must know how to call a function, and loop. Instructors: Vinicius Pantoja and Kashiap Murali, Princeton School of AI Computer Vision (April) - This module will focus on a field where there has been loads of recent developments, Computer Vision (CV). Self driving cars, object detection, flower classification, etc. all fall into this wide and interesting bucket. You will learn how to analyze an image and classify it into different categories by capturing the image, preprocessing the image, and finally, building a model that is trained on these images and can classify new ones. We will also briefly explore the cyber security risks associated with Computer Vision and discuss industry trends. Part 1: Business Overview and Basic Implementation Wednesday April 3, 6-8pm Part 2: Convolutional Neural Networks 1 (identifying objects) Wednesday April 10, 6-8pm Part 3: Convolutional Neural Networks 2 Wednesday April 17, 6-8pm Part 4: Capstone Wednesday April 24, 6-7pm

Past events (69)

AI: (NLP) Recommendation System NLP

Needs a location

Photos (246)