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#Linear Models

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Massachusetts Institute of Technology

Feedback Control from Pixels

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Explore feedback control using cameras, bridging control theory and machine learning. Learn about challenges, recent advances, and potential applications in robotics and AI.
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38 Lesons
1 hour 2 minutes
On-Demand
Free-Video
California Institute of Technology

Machine Learning Course

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Comprehensive exploration of machine learning fundamentals, covering linear models, neural networks, SVMs, and key principles for effective algorithm implementation and evaluation.
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18 Lesons
1 day
On-Demand
Free-Video

Linear Regression and Linear Models

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Learn powerful statistical tools: linear regression and models. Predict continuous values using various data types. Covers least squares, multiple regression, t-tests, ANOVA, and R implementation.
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10 Lesons
1 hour 30 minutes
On-Demand
Free-Video
Institute for Pure & Applied Mathematics (IPAM)

Comparison and Transfer Between Tasks in Overparameterized Learning

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Explore similarities and differences in classification and regression tasks for overparameterized linear models. Gain insights into task transfer and generalization in high-dimensional regimes.
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1 Lesons
49 minutes
On-Demand
Free-Video
BioinformaticsDotCA

CBW's Introduction to R Workshop - June 21-22, 2021

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Learn R programming essentials: scripting, statistical tests, loops, functions, linear models, and R Markdown in this comprehensive workshop for beginners.
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6 Lesons
10 hours
On-Demand
Free-Video
Jonathan Walters

Differential Equations

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Explore differential equations through various techniques, including separation of variables, integrating factors, exact equations, series solutions, Laplace transforms, and systems of linear equations.
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27 Lesons
3 hours 30 minutes
On-Demand
Free-Video
Jonathan Walters

First Order Differential Equations

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Learn to solve various types of first-order differential equations, including linear, exact, and Bernoulli equations, with applications and practical problem-solving techniques.
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6 Lesons
30 minutes
On-Demand
Free-Video

Learn Statistics with Python

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Master Python for statistical analysis: design matrices, linear models, F distribution, and OLS. Hands-on tutorials using Orange and Patsy libraries for practical data science skills.
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4 Lesons
1 hour 30 minutes
On-Demand
Free-Video

PyTorch Zero to All

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Learn essential machine learning and deep learning concepts using PyTorch, covering linear models, neural networks, CNNs, and RNNs in a comprehensive series of lectures.
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14 Lesons
3 hours 30 minutes
On-Demand
Free-Video

PyTorch for Python 3.5

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Learn PyTorch fundamentals, from linear models to advanced CNNs. Master gradient descent, back-propagation, regression, and neural network architectures for efficient deep learning implementation.
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14 Lesons
2 hours 30 minutes
On-Demand
Free-Video
Centre de recherches mathématiques - CRM

Lower and Upper Bounds on the VC-Dimension of Tensor Network Models

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Explorez les limites de la dimension VC des modèles de réseaux de tenseurs. Apprenez les bornes supérieures et inférieures pour divers modèles de décomposition tensorielle et leurs implications pour l'apprentissage automatique.
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14 Lesons
53 minutes
On-Demand
Free-Video
Simons Institute

What Does It Take to Be a Good Fisherman?

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Explore statistical challenges in learning from biased data, focusing on self-selection issues in various fields and discussing recent progress in econometric modeling and auction theory.
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17 Lesons
1 hour 7 minutes
On-Demand
Free-Video
Julia Silge

Use Tidymodels Workflowsets to Predict Human-Computer Interactions from Star Trek

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Explore machine learning with tidymodels workflowsets to predict speaker type in Star Trek interactions, featuring data preprocessing, model evaluation, and result analysis.
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9 Lesons
32 minutes
On-Demand
Free-Video
Julia Silge

Predict Housing Prices in Austin TX with Tidymodels and XGBoost

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Explore feature engineering for boosted tree models using Austin housing data. Learn to incorporate text information as indicator variables and tune models for accurate price predictions.
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18 Lesons
52 minutes
On-Demand
Free-Video
NPTEL-NOC IITM

Gauss-Markov Theorem

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Explore the fundamental principles and applications of the Gauss-Markov theorem in statistical analysis and linear regression modeling.
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1 Lesons
23 minutes
On-Demand
Free-Video
ICTP Mathematics

Some Geometric Properties of Spacetime - Lecture 3

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Explore geometric properties of spacetime, including minimal hypersurfaces, stability, and boundary integrals. Gain insights into linear and nonlinear models in this advanced mathematics lecture.
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15 Lesons
1 hour 16 minutes
On-Demand
Free-Video
LiquidBrain Bioinformatics

Running Basic Statistical Analysis in R

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Learn to perform essential statistical analyses in R, including correlation, linear modeling, t-tests, and heatmaps. Ideal for beginners seeking to leverage R's powerful command-line interface for data analysis.
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7 Lesons
23 minutes
On-Demand
Free-Video
UofU Data Science

Linear Models and Their Geometry in Machine Learning - Lecture 6

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Explore the geometry and fundamental concepts of linear classifiers, examining their role as essential tools in machine learning classification problems.
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1 Lesons
33 minutes
On-Demand
Free-Video
UofU Data Science

Linear Classifier Expressiveness in Machine Learning - Lecture 7

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Delve into the theoretical foundations of linear classifiers, exploring their expressive capabilities and understanding their role as a fundamental hypothesis class in machine learning.
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1 Lesons
43 minutes
On-Demand
Free-Video
Simons Institute

Reconsidering Overfitting in the Age of Overparameterized Models

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Explore modern machine learning paradigms, focusing on overparameterized models' ability to generalize well despite near-zero training error, challenging classical overfitting concepts.
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1 Lesons
1 hour 18 minutes
On-Demand
Free-Video
Simons Institute

What Is the Statistical Complexity of Reinforcement Learning?

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Explore statistical complexity in reinforcement learning, covering supervised learning, linear models, evaluation challenges, and realizability conditions.
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13 Lesons
30 minutes
On-Demand
Free-Video
Hausdorff Center for Mathematics

Generalization in Deep Learning Through the Lens of Implicit Rank Minimization

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Explores implicit regularization in deep learning through matrix and tensor factorizations, revealing tendencies towards low ranks. Discusses implications for generalization and potential improvements in neural network design.
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24 Lesons
41 minutes
On-Demand
Free-Video
Simons Institute

In-Context Learning: A Case Study of Simple Function Classes

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Exploring in-context learning capabilities of AI models, focusing on Transformers and LSTMs for learning basic function classes, with insights on evaluation and architectural differences.
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1 Lesons
1 hour 4 minutes
On-Demand
Free-Video
Simons Institute

When Is Scale Enough?

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Exploring performance predictability in deep learning as models and datasets scale up, focusing on large language models and investigating solvable problems through scaling alone.
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1 Lesons
1 hour 12 minutes
On-Demand
Free-Video
Hackaday

Quantum Computing - Guest Lecture

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Explore quantum machine learning with Dr. Maria Schuld, covering linear models, deep learning, quantum software, and the intersection of quantum computing and AI.
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17 Lesons
50 minutes
On-Demand
Free-Video
BSidesLV

No Silver Bullet - Multi Contextual Threat Detection via Machine Learning

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Explore multi-contextual threat detection using machine learning, covering big data processing, modeling adversaries, and building custom solutions for defense at scale.
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23 Lesons
53 minutes
On-Demand
Free-Video
EuroPython Conference

Explaining Behavior of Machine Learning Models with ELI5 Library

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Explore techniques for interpreting and debugging ML models using eli5 library. Learn to explain linear models, decision trees, ensembles, and classifiers, improving trust and quality in ML solutions.
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1 Lesons
30 minutes
On-Demand
Free-Video
UofU Data Science

Linear Models and Their Geometry in Machine Learning - Lecture 5

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Explore the fundamental concepts and geometric principles behind linear classifiers, a cornerstone of machine learning algorithms and classification techniques.
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1 Lesons
21 minutes
On-Demand
Free-Video
Toronto Machine Learning Series (TMLS)

The Importance of Intelligibility in Machine Learning for Healthcare - Avoiding Black-Box Models

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Explore intelligible machine learning models for healthcare, balancing accuracy and interpretability. Learn to understand, validate, and edit models for safe deployment in critical applications.
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1 Lesons
51 minutes
On-Demand
Free-Video
Google TechTalks

Mapping from Training Data to Predictions with Datamodels - Differential Privacy in Machine Learning

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Explore datamodels in machine learning, from training data to predictions. Learn about model brittleness, data counterfactuals, and applications in ML pipelines.
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17 Lesons
59 minutes
On-Demand
Free-Video
Imperial College London

Learning Linear Models In-Context with Transformers

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Explore in-context learning of linear models using transformers with UC Davis professor Spencer Frei in this insightful seminar.
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1 Lesons
1 hour 10 minutes
On-Demand
Free-Video
Manolis Kellis

Training Neural Networks and Deep Learning Optimization Methods - Lecture 16

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Master neural network training fundamentals, from momentum methods and regularization to batch normalization, with practical applications in BBB transmission prediction and model optimization.
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9 Lesons
1 hour 17 minutes
On-Demand
Free-Video
UofU Data Science

Linear Models and Linear Classifiers - Lecture 6

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Delve into linear classifiers and their expressive hypothesis class, exploring augmented versions, monotone conjunctions, and feature transformations for machine learning applications.
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10 Lesons
1 hour 5 minutes
On-Demand
Free-Video
UofU Data Science

Predictive Distribution and Model Comparison in Linear Models - Lecture 12

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Dive into predictive distribution modeling, exploring linear models, binary classification, and logistic regression while mastering maximum molecular estimation techniques.
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9 Lesons
1 hour 19 minutes
On-Demand
Free-Video