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Data Science Interview Handbook

Data Science Interview Handbook

The ultimate guide to data science interviews. Developed by FAANG engineers, it covers Python, algorithms, ML concepts, and interview questions. Get interview-ready in just a few hours.

Machine Learning System Design

Machine Learning System Design

Gain insights into ML system design, state-of-the-art techniques, and best practices for scalable production. Learn from top researchers and stand out in your next ML interview.

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.

Hands-on Machine Learning with Scikit-Learn

Hands-on Machine Learning with Scikit-Learn

Gain insights into Scikit-Learn's datasets, feature engineering, linear/logistic regression, and unsupervised learning. Delve into k-means clustering and neural networks to enhance your machine learning expertise.

Applied Machine Learning: Industry Case Study with TensorFlow

Applied Machine Learning: Industry Case Study with TensorFlow

Gain insights into predicting retail sales with TensorFlow. Delve into data analysis, training models, and extracting insights using industry techniques. Explore efficient model evaluation with experts from top tech companies.

A Beginner's Guide to Deep Learning

A Beginner's Guide to Deep Learning

Gain insights into deep learning fundamentals, explore perceptron and advanced models, and discover practical coding in NumPy and Keras. Test your knowledge with quizzes and coding challenges.

Introduction to Deep Learning & Neural Networks

Introduction to Deep Learning & Neural Networks

Gain insights into basic and intermediate deep learning concepts, including CNNs, RNNs, GANs, and transformers. Delve into fundamental architectures to enhance your machine learning model training skills.

Machine Learning with NumPy, pandas, scikit-learn, and More

Machine Learning with NumPy, pandas, scikit-learn, and More

Delve into practical machine learning with NumPy, pandas, scikit-learn, and more. Gain insights into data analysis, feature engineering, and deep learning using industry-standard frameworks. Basic Python required.