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Machine Learning Basics

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Related lectures (41)

Overfitting in Supervised Learning: Case Studies and Techniques Log in to Mediaspace to watch this video

Addresses overfitting in supervised learning through polynomial regression case studies and model selection techniques.

Linear Regression: Basics and Estimation Log in to Mediaspace to watch this video

Covers the basics of linear regression and how to solve estimation problems using least squares and matrix notation.

Supervised Learning in Financial Econometrics Log in to Mediaspace to watch this video

Explores supervised learning in financial econometrics, covering linear regression, model fitting, potential problems, basis functions, subset selection, cross-validation, regularization, and random forests.

Linear Regression: Basics Log in to Mediaspace to watch this video

Covers the basics of linear regression, binary and multi-class classification, and evaluation metrics.

Binary Classification by Regression: Decision Functions and Cost Functions Log in to Mediaspace to watch this video

Explores binary classification by regression, decision functions, and various cost functions.

Machine Learning Review Log in to Mediaspace to watch this video

Covers a review of machine learning concepts, including supervised learning, classification vs regression, linear models, kernel functions, support vector machines, dimensionality reduction, deep generative models, and cross-validation.

Linear Regression: Basics and Gradient Descent Log in to Mediaspace to watch this video

Covers the basics of linear regression, including feature engineering, supervised vs. unsupervised learning, and minimizing the cost function.

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

Explores linear regression fundamentals, model training, evaluation, and performance metrics, emphasizing the importance of R², MSE, and MAE.

Supervised Learning: Likelihood Maximization Log in to Mediaspace to watch this video

Covers supervised learning through likelihood maximization to find optimal parameters.

Linear Regression and Logistic Regression Log in to Mediaspace to watch this video

Covers linear and logistic regression for regression and classification tasks, focusing on loss functions and model training.

Linear Programming: Convex Hull Log in to Mediaspace to watch this video

Covers MAE regression, convex hull, reformulation advantages, and practical problems with decision variables and constraints.

Safe Machine Learning: Cryptographic Opportunities Log in to Mediaspace to watch this video

Explores the intersection between machine learning and cryptography, focusing on safe machine learning through cryptographic tools and models.

Data Science Essentials: Pandas, Numpy, Matplotlib Log in to Mediaspace to watch this video

Introduces Pandas, Numpy, and Matplotlib for data analysis and visualization in Python.

Sparse Regression Log in to Mediaspace to watch this video

Covers the concept of sparse regression and the use of Gaussian additive noise in the context of MAP estimator and regularization.

Optimization in Machine Learning Log in to Mediaspace to watch this video

Explores optimization techniques, word embeddings, and recommendation systems in machine learning.

Distributed Information Systems: Overview and Models Log in to Mediaspace to watch this video

Covers Distributed Information Systems, key tasks, methods, projects, evaluation, and exam support.

NABEL Data Analysis Log in to Mediaspace to watch this video

Covers the NABEL Data Analysis Assignment, emphasizing data analysis skills and report formatting for air pollution concentrations and meteorology.

Neuro-symbolic Representations: Commonsense Knowledge & Reasoning Log in to Mediaspace to watch this video

Explores neuro-symbolic representations for understanding commonsense knowledge and reasoning, emphasizing the challenges and limitations of deep learning in natural language processing.

Machine Learning and Privacy Log in to Mediaspace to watch this video

Explores Federated Machine Learning and Differential Privacy in Machine Learning, discussing attacks, defenses, and challenges.

Machine Learning Models for Neuroscience Log in to Mediaspace to watch this video

Explores machine learning models for neuroscience, focusing on understanding brain function and core object recognition through convolutional neural networks.

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