Feature Engineering: Fundamentals and Best PracticesA summary of Chapter 5 of the Book “Designing Machine Learning Systems” by Chip HuyenApr 12, 2024Apr 12, 2024
Analysis of chapter 0 of the book “The Principles of Deep Learning Theory”This perspective leads us to consider that neural networks are governed by nearly-gaussian distributions.Apr 12, 2024Apr 12, 2024
10 key points of Chapter 4 of Chip Huyen’s book, “Designing Machine Learning Systems”Training data serves as the cornerstone of machine learning algorithms, dictating their effectiveness and reliability. Chapter 4 of the…Apr 5, 2024Apr 5, 2024
“On the Societal Impact of Open Foundation Models” —My Personal ReviewThe favorable aspects and the drawbacks of model sharingApr 5, 2024Apr 5, 2024
Designing Machine Learning Systems: A Brief Summary of Chapters 1–3The development of machine learning systems is a multifaceted process that encompasses far more than just algorithmic considerations. The…Mar 21, 2024Mar 21, 2024
Summary of chapter 3: Data Engineering FundamentalsChapter 3 covers the fundamentals of data engineering and provides a detailed look at the different steps and considerations involved in…Mar 21, 2024Mar 21, 2024
Summary of chapter 2: Introduction to Machine Learning Systems DesignChapter 2 introduces the design of machine learning systems by adopting a systematic approach to MLOps. It highlights the importance of…Mar 21, 2024Mar 21, 2024
Summary of chapter 1: Overview Of Machine Learning SystemsChapter 1, “Overview Of Machine Learning Systems” offers a comprehensive overview of machine learning systems and their rise from deep…Mar 21, 2024Mar 21, 2024
Transfer Learning on NLP using TensorFlowUsing the models from TensorFlowHub, Fine Tuning them, comparing these models with a model trained from scratch and creating a hybrid modelDec 17, 2020Dec 17, 2020
Using the AlexNet on a Cat-Dog classificationWith Hyperparameter tuning and Data AugmentationNov 30, 2020Nov 30, 2020
