Ace your machine learning interviews with Exponent’s ML engineer interview course: https://bit.ly/3SSbxC4 A machine learning engineer demonstrates the process of building a system to classify tweets as harmful or not. The engineer explores the dataset, emphasizing data pre-processing and tokenization using a pre-trained tokenizer. A sequential model architecture is chosen with layers for embedding, LSTM, and non-linearity, and their roles are explained. The engineer discusses monitoring training and validation loss to detect overfitting or underfitting and suggests countermeasures. For evaluation, metrics like precision, recall, and accuracy are proposed, considering the dataset's imbalance. The engineer acknowledges the potential benefits of using a different model architecture like BERT and highlights the importance of evaluating model calibration and interpretability aspects. Chapters (Powered by ChapterMe) - 00:00 - Introduction to Building a Toxic Tweet Classification System 01:53 - Overview of Binary Classification and Predictions 02:59 - Model Deployment and Monitoring 05:11 - Text Classification: Preprocessing Pipeline 08:46 - Balancing Dataset Samples 11:27 - Advanced Preprocessing for Machine Learning 22:23 - Building a Sequential Model with Keras 28:15 - Understanding LSTM Layers for Contextual Information 31:31 - Model Summary: Training, GPU Use, and Loss Function 34:29 - Model Training Strategies and Overfitting Prevention 38:47 - Evaluating Model Precision and Recall 43:09 - Automated Sentiment Processing with Instant Models 46:31 - Leveraging BERT Tokens for Classification 48:24 - Fundamentals of Machine Learning and Model Validation Want more machine learning content? - Fake News Detection System - Machine Learning Mock Interview - https://youtu.be/qrNqUwpypT8 - Amazon Machine Learning Engineer Interview: K-Means Clustering - https://youtu.be/xKZHH-UOsUM - How to Become a Machine Learning Engineer - https://youtu.be/VP8eC3I1IHQ 👉 Subscribe to our channel: http://bit.ly/exponentyt 🕊️ Follow us on Twitter: http://bit.ly/exptweet 💙 Like us on Facebook for special discounts: http://bit.ly/exponentfb 📷 Check us out on Instagram: http://bit.ly/exponentig 📹 Watch us on TikTok: https://bit.ly/exponenttiktok ABOUT US: Did you enjoy this interview question and answer? Want to land your dream career? Exponent is an online community, course, and coaching platform to help you ace your upcoming interview. Exponent has helped people land their dream careers at companies like Google, Microsoft, Amazon, and high-growth startups. Exponent is currently licensed by Stanford, Yale, UW, and others. Our courses include interview lessons, questions, and complete answers with video walkthroughs. Access hours of real interview videos, where we analyze what went right or wrong, and our 1000+ community of expert coaches and industry professionals, to help you get your dream job and more!