Talks at Ada: Machine Learning, Productivity, and Technical Leadership

This is a past event

86 people went

Location image of event venue

Details

Ada is a chatbot that solves more than 70% of inquiries, using machine learning for natural language processing. We have a lineup of amazing talks by developers and leads at Ada! Product and Machine Learning engineers alike will be sharing their lessons on being more effective at work, or their latest research.

Schedule:

6:00PM - 6:30PM : Sign-In & Networking
6:30PM – 7:45PM : Speaker Talks
7:45PM – 8:00PM : Audience Q/A
8:00PM – 8:30PM : Networking & Wrap Up

Talk #1: Transfer Learning for NLP: Distilling Sebastien Ruder's PhD. thesis

Transfer learning, the act of applying knowledge from one problem to another, has become one of the most important research areas of machine learning for Natural Language Processing (NLP). Gordon will use Sebastien Ruder's recently published PhD thesis on transfer learning for NLP as a guide through the field, and will show you some ways you can easily apply transfer learning to your own projects.

Speaker: Gordon Gibson is the lead machine learning engineer at Ada where he works on developing machine learning applications which are both practical and thoughtfully-designed.

Talk #2: BuJo 101: On Note-Taking and Bullet Journals

Despite the fact that we're living through the Fourth Industrial Revolution, note-taking by hand remains a valuable skill. This talk will focus on how to take better notes using the BuJo system, and why it can serve you well in both in your personal and professional lives.

Speaker: Althea Yi is a full-stack developer at Ada, currently working on levelling up her back-end skills.

Talk #3: Better code without code: Framework for Understanding What You Really Need to Solve

You see a ticket. You push some code in record time. You feel like a genius. Hours later your peer suggests a few updates. You say, "Hmm, should've thought of that". Days later, testers come in and file a few bugs. "Should've caught that" you utter. Weeks later, users are filing bugs left and right. "Well !@^%", you say. The next ticket comes in and the cycle repeats itself. It's not just you. It's all of us. Now, what can we do about it? Asking some simple key questions before you code can dramatically improve it.

Speaker: Kris Anthony Viceral is the tech lead for Ada's automation team. They work with other team members to understand what's slowing them down, and build solutions so that they can work faster and better.

Talk #4: Tu Konkani Ulaytai? Building Language Identifiers with Machine Learning

One of the first tasks that any Natural Language Processing (NLP) models perform is language identification of the input text. Once the language of the text is identified, individual NLP models (such as translators, speech synthesizers etc.,) can then be employed to perform an NLP activity. In this talk, I will present the historical background of language identification and show how to build a simple language identifier that can detect a variety of languages.

Speaker: Royal Sequeira is a Machine Learning Developer at Ada and works on improving the Natural Language Understanding of Ada's bots.