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Related lectures (58)

Deep Learning Fundamentals Log in to Mediaspace to watch this video

Introduces deep learning fundamentals, covering data representations, neural networks, and convolutional neural networks.

Boltzmann Machine Log in to Mediaspace to watch this video

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PyTorch and Convolutional Networks Log in to Mediaspace to watch this video

Covers PyTorch tensor data structure and training a CNN to classify images.

Principal Component Analysis: Eigenfaces Log in to Mediaspace to watch this video

Covers the application of Principal Component Analysis in facial recognition using a famous faces dataset.

Machine Learning Basics Log in to Mediaspace to watch this video

Covers the basics of machine learning, including supervised and unsupervised techniques, linear regression, and model training.

Spectral Estimation Methods Log in to Mediaspace to watch this video

Explores parametric spectrum estimation methods, including line and smooth spectra, and delves into heart rate variability analysis.

Regression Trees and Ensemble Methods in Machine Learning Log in to Mediaspace to watch this video

Discusses regression trees, ensemble methods, and their applications in predicting used car prices and stock returns.

Logistic Regression: Fundamentals and Applications Log in to Mediaspace to watch this video

Explores logistic regression fundamentals, including cost functions, regularization, and classification boundaries, with practical examples using scikit-learn.

Memory Management & Crash Programs Log in to Mediaspace to watch this video

Covers memory management for engineers, focusing on crash programs related to memory access errors.

Deep Learning: Data, Models, and Challenges Log in to Mediaspace to watch this video

Provides an overview of deep learning concepts, focusing on data, model architecture, and challenges in handling large datasets.

Data Representations and Processing in Machine Learning Log in to Mediaspace to watch this video

Covers data representations and processing techniques essential for effective machine learning algorithms.

Data-Driven Modeling in Neuroscience: Meenakshi Khosla Log in to Mediaspace to watch this video

By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.

Deep Learning: Multilayer Perceptron and Training Log in to Mediaspace to watch this video

Covers deep learning fundamentals, focusing on multilayer perceptrons and their training processes.

Deep Learning: Principles and Applications Log in to Mediaspace to watch this video

Covers the fundamentals of deep learning, including data, architecture, and ethical considerations in model deployment.

Clustering & Density Estimation Log in to Mediaspace to watch this video

Covers clustering, PCA, LDA, K-means, GMM, KDE, and Mean Shift algorithms for density estimation and clustering.

Machine Learning: Supervised and Unsupervised Learning Techniques Log in to Mediaspace to watch this video

Covers supervised and unsupervised learning techniques in machine learning, highlighting their applications in finance and environmental analysis.

Clustering & Density Estimation Log in to Mediaspace to watch this video

Covers dimensionality reduction, PCA, clustering techniques, and density estimation methods.

Untitled Log in to Mediaspace to watch this video

Statistical Signal Processing Log in to Mediaspace to watch this video

Covers Gaussian Mixture Models, Denoising, Data Classification, and Spike Sorting using Principal Component Analysis.

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