Machine Learning Algorithms in Depth av Vadim Smolyakov

<h3>Develop a mathematical intuition around machine learning algorithms to improve model performance and effectively troubleshoot complex ML problems.</h3> <p>For intermediate machine learning practitioners familiar with linear algebra, probability, and basic calculus.</p> <p><strong>Machine Learning Algorithms in Depth</strong> dives into the design and underlying principles of some of the most exciting machine learning (ML) algorithms in the world today.</p> <p>With a particular emphasis on probability-based algorithms, you will learn the fundamentals of Bayesian inference and deep learning. You will also explore the core data structures and algorithmic paradigms for machine learning.</p> <p>You will explore practical implementations of dozens of ML algorithms, includin</p> <ul> <li>Monte Carlo Stock Price Simulation</li> <li>Image Denoising using Mean-Field Variational Inference</li> <li>EM algorithm for Hidden Markov Models</li> <li>Imbalanced Learning, Active Learning and Ensemble Learning</li> <li>Bayesian Optimisation for Hyperparameter Tuning</li> <li>Dirichlet Process K-Means for Clustering Applications</li> <li>Stock Clusters based on Inverse Covariance Estimation</li> <li>Energy Minimisation using Simulated Annealing</li> <li>Image Search based on ResNet Convolutional Neural Network</li> <li>Anomaly Detection in Time-Series using Variational Autoencoders</li> </ul> <p>Each algorithm is fully explored with both math and practical implementations so you can see how they work and put into action.</p> <h4>About the technology</h4> <p>Fully understanding how machine learning algorithms function is essential for any serious ML engineer. This vital knowledge lets you modify algorithms to your specific needs, understand the trade-offs when picking an algorithm for a project, and better interpret and explain your results to your stakeholders. This unique guide will take you from relying on one-size-fits-all ML libraries to developing your own algorithms to solve your business needs.</p>