Principal Component Analysis: Olympic Medals & Image Compression

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Explores challenges in distributed computing, data growth, and data types, emphasizing the battle against the three Vs in big data.

Covers the implementation of fully connected neural networks on two datasets using PyTorch.

Explores machine learning for predicting new product life cycles and the challenges of limited historical data.

Covers bivariate data analysis, correlation, and regression techniques, including interpretation of coefficients and least squares geometry.

Explores the significance of data models in scientific research and the challenges posed by big data.

Covers data wrangling stages, structuring techniques, and common issues in data preparation.

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