A Glimpse of NLP in Industry Bo HAN (bo.a. .au) 24/05/2021 mailto:bo.a. .au Outline ● My Journey & motivations (5 mins) ● Use Case: Geolocation Prediction (20 mins) ● Academia and Industry comparisons (5 mins) ● NLP landscape in industry applications (10 mins) ● Mindset for Industry (10 mins) ● Questions and Answers (10 mins) […]
Concurrency for Software Development Presented by Dr. Shuaiwen Leon Song USYD Future System Architecture Lab (FSA) https://shuaiwen-leon-song.github.io/ https://shuaiwen-leon-song.github.io/ Tips for students joining online – Remember that you are still in a space with other students. – Mute your microphone when not speaking. – Use earphones or headphones – the mic is better and you’ll disturb
6c_Data_Science.dvi COMP9414 Data Science 1 Overview � Methodology � Bias � Overfitting � Combining Datasets � Slicing and Dicing � Validation UNSW ©W. Wobcke et al. 2019–2021 COMP9414: Artificial Intelligence Lecture 6c: Data Science Wayne Wobcke e-mail:w. .au UNSW ©W. Wobcke et al. 2019–2021 COMP9414 Data Science 3 Feature Engineering Example: Mobile Phone Data includes
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Lecture 9: Neural Networks COMP90049 Introduction to Machine Learning Semester 1, 2020 Lea Frermann, CIS 1 Roadmap So far … Classification and Evaluation • Naive Bayes, Logistic Regression, Perceptron • Probabilistic models • Loss functions, and estimation • Evaluation Today… Neural Networks • Multilayer Perceptron • Motivation and architecture • Linear vs. non-linear classifiers 2
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l6-hmm-v2 COPYRIGHT 2021, THE UNIVERSITY OF MELBOURNE 1 Semester 1 2021 Week 3 Jey Han Lau Sequence Tagging: Hidden Markov Models COMP90042 Natural Language Processing Lecture 6 COMP90042 L6 2 POS Tagging Recap • Janet will back the bill • Janet/NNP will/MB back/VP the/DT bill/NN • Local classifier: prone to error propagation • What about
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l19-qa-v3 COPYRIGHT 2021, THE UNIVERSITY OF MELBOURNE 1 COMP90042 Natural Language Processing Lecture 19 Semester 1 2021 Week 10 Jey Han Lau Question Answering COMP90042 L19 2 Introduction • Definition: question answering (“QA”) is the task of automatically determining the answer for a natural language question • Mostly focus on “factoid” questions COMP90042 L19 3
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l18-information-extraction-v3 COPYRIGHT 2021, THE UNIVERSITY OF MELBOURNE 1 COMP90042 Natural Language Processing Lecture 18 Semester 1 2021 Week 9 Jey Han Lau Information Extraction COMP90042 L18 2 Information Extraction • Given this: ‣ “Brasilia, the Brazilian capital, was founded in 1960.” • Obtain this: ‣ capital(Brazil, Brasilia) ‣ founded(Brasilia, 1960) • Main goal: turn text
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l1-intro-v2 COPYRIGHT 2021, THE UNIVERSITY OF MELBOURNE 1 Course Overview & Introduction COMP90042 Natural Language Processing Lecture 1 Semester 1 2021 Week 1 Jey Han Lau COMP90042 L1 2 Prerequisites • COMP90049 “Introduction to Machine Learning” or COMP30027 “Machine Learning” ‣ Modules → Welcome → Machine Learning Readings • Python programming experience • No
Lecture 8: The Perceptron COMP90049 Introduction to Machine Learning Semester 1, 2020 Lea Frermann, CIS 1 Introduction Roadmap So far… Naive Bayes and Logistic Regression • Probabilistic models • Maximum likelihood estimation • Examples and code Today… The Perceptron • Geometric motivation • Error-based optimization • …towards neural networks 2 Roadmap So far… Naive Bayes
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07-deep-learning Deep Learning with keras¶ In this workshop, we will try to build some feedforward models to do sentiment analysis, using keras, a deep learning library: https://keras.io/ You will need pandas, keras (2.3.1) and tensorflow (2.1.0; and their dependencies) to run this code (pip install pandas keras==2.3.1 tensorflow-cpu==2.1.0). First let’s prepare the data. We are
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