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Reliable Machine Learning

Reliable Machine Learning

Explore how to ensure reliability in ML models. Gain insights into software testing, ML-specific techniques, runtime checks, and monitoring tools to build robust ML systems effectively.

Building a Machine Learning Pipeline from Scratch

Building a Machine Learning Pipeline from Scratch

Learn about ML pipeline development, delve into best practices, discover advanced Python concepts, and explore testing methodologies to elevate your software engineering skills and career prospects.

Grokking the Machine Learning Interview

Grokking the Machine Learning Interview

Your proven path to success in Machine Learning Interviews – developed by FAANG engineers. Unlock ML loops at top companies with a System Design approach.

Machine Learning Handbook

Machine Learning Handbook

Gain insights into ML fundamentals, explore Python libraries, and delve into real-world applications like Tesla and ChatGPT. Discover traditional vs. deep learning for data-driven decision-making.

Fundamentals of Machine Learning: A Pythonic Introduction

Fundamentals of Machine Learning: A Pythonic Introduction

Learn machine learning with scikit-learn, covering supervised learning, clustering, regression, SVMs, autoencoders, and ensemble methods through practical Python projects.

A Practical Guide to Machine Learning with Python

A Practical Guide to Machine Learning with Python

Explore practical coding of basic machine learning models using Python. Gain insights into algorithms like linear regression, logistic regression, SVM, KNN, and decision trees.