From module to module the paths lets you dive deeper into the technical details. At end you should understand and be able to explain the functionings of machine learning.

Curated by Camillo

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Overview

From module to module the paths lets you dive deeper into the technical details. At end you should understand and be able to explain the functionings of machine learning.

Curated by Camillo

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Mathematical discussion of Linear Regression, Logistic Regression, Neural Networks, Support Vector Machines

This course provides you with a profound insight on the technicalities of important machine learning algorithm!

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Iterative algorithm to find a min / max of a function, optimization strategy, iteratively moving in the direction of steepest descent

How does a machine learn? This algorithm is at the hearth of learning!

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Fitting data too closely or exactly to a particular dataset, and may therefore fail to fit unseen data

This is one of most common problems in applied machine learning!

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Linear algebra, multivariate calculus, principal component analysis

If you are interested at the mathematical details, take this course!

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"When a measure becomes a target, it ceases to be a good measure."

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Research insights

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Modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering

This best selling book dives deeper into relevant concepts of machine learning!

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Dissecting papers, explanation of the intuition and theory, aggregating resources, computer vision, deep learning, natural language processing

Articles on advanced ML concepts

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Curated implementations of machine learning models in pytorch, tensor flow, caffe2, computer vision, natural language processing

This platform entails papers that present solutions to various machine learning tasks from a theoretical and practical perspective.