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Neural Networks Demystified

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In this short series, we will build and train a complete Artificial Neural Network in python.
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7 Lesons
30 minutes
On-Demand
Free-Video

Neural Networks

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This playlist has everything you need to know about Neural Networks, from the basics, all the way to image classification with Convolutional Neural Networks.
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13 Lesons
3 hours 30 minutes
On-Demand
Free-Video

Gradient Boost

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Explore the fundamentals and advanced concepts of Gradient Boost for regression and classification in machine learning.
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4 Lesons
1 hour 30 minutes
On-Demand
Free-Video
NPTEL

Practical Machine Learning with Tensorflow

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Learn essential machine learning concepts and apply them using TensorFlow, covering key topics from basic principles to deep learning and data visualization.
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10 Lesons
4 hours 30 minutes
On-Demand
Free-Video
University of Central Florida

Lucas-Kanade Tracker (KLT) - Global Motion Estimation - Lecture 10

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Explore Lucas-Kanade Tracker (KLT) for computer vision, covering global motion estimation, object tracking, and 2D transformations. Gain insights into advanced tracking algorithms.
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19 Lesons
1 hour 14 minutes
On-Demand
Free-Video
University of Central Florida

CAP5415 - Training Neural Networks Part 2 - Fall 2020 - Lecture 7

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Explore advanced neural network training techniques, including loss functions, backpropagation, gradient descent optimization, and strategies to address common challenges in deep learning.
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18 Lesons
1 hour 2 minutes
On-Demand
Free-Video
University of Central Florida

CAP5415 - Training Neural Networks Part 1 - Lecture 7 - Fall 2020

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Explore neural network training techniques, including learning kernels, loss functions, and gradient descent, to enhance your understanding of deep learning fundamentals.
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6 Lesons
25 minutes
On-Demand
Free-Video
University of Central Florida

Training Neural Networks for Computer Vision - Part I - Lecture 10

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Explore neural network training techniques, including gradient descent, loss functions, and backpropagation, for effective computer vision model optimization and performance improvement.
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13 Lesons
36 minutes
On-Demand
Free-Video
Broad Institute

The Challenges of Training Infinitely Large Neural Networks

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Explore challenges in training infinitely large neural networks with Mikhail Belkin. Gain insights into foundational advances in machine learning for biomedical applications.
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1 Lesons
1 hour 6 minutes
On-Demand
Free-Video
Great Learning

Stochastic Gradient Descent

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Explore stochastic gradient descent, its advantages, and implementation. Learn about mini-batches, momentum, and convergence in this optimization algorithm for machine learning models.
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14 Lesons
1 hour 37 minutes
On-Demand
Free-Video
Great Learning

Artificial Intelligence Tutorial for Beginners - AI Full Course

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Keeping the importance of artificial intelligence in mind, we have come up with this full course on Artificial Intelligence.
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10 Lesons
7 hours 12 minutes
On-Demand
Free-Video

Complete Deep Learning

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Comprehensive deep learning course covering neural networks, CNN, RNN, LSTM, and advanced topics with hands-on tutorials and practical implementations.
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88 Lesons
1 day 6 hours
On-Demand
Free-Video

Introduction to Deep Learning for Everyone

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Learn deep learning fundamentals using Keras and TensorFlow in R, covering regression, neural networks, regularization, and convolutional networks for practical applications.
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22 Lesons
7 hours
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
Great Learning

Artificial Intelligence Projects

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Explore AI projects using neural networks for bank default prediction, stock forecasting, and image processing. Learn CNN, RNN, and time series analysis techniques.
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9 Lesons
3 hours 34 minutes
On-Demand
Free-Video
Great Learning

Bank Defaulters Using ANN

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Learn to build and apply Artificial Neural Networks for predicting bank defaulters using Keras, covering ANN architecture, activation functions, backpropagation, and practical demonstrations.
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11 Lesons
1 hour 18 minutes
On-Demand
Free-Video
The Julia Programming Language

Seam Carving and Dynamic Programming - Week 2 - MIT Fall 2020

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Explore seam carving algorithm for intelligent image resizing, covering edge detection with gradients and optimal path finding using dynamic programming.
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5 Lesons
28 minutes
On-Demand
Free-Video
Python Engineer

Deep Learning With PyTorch - Full Course

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Comprehensive PyTorch tutorial covering fundamentals, advanced concepts, and practical implementations for deep learning, from tensor basics to CNNs and transfer learning.
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18 Lesons
4 hours 36 minutes
On-Demand
Free-Video
Krish Naik

Deep Learning - All Optimizers in One Video - SGD with Momentum, Adagrad, Adadelta, RMSprop, Adam Optimizers

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Comprehensive exploration of deep learning optimizers, covering gradient descent, SGD, momentum, Adagrad, Adadelta, RMSprop, and Adam, with detailed explanations and comparisons.
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6 Lesons
1 hour 42 minutes
On-Demand
Free-Video
3Blue1Brown

Gradient Descent, How Neural Networks Learn

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Explore gradient descent and neural network learning through animations, examples, and expert insights. Gain a deeper understanding of cost functions, network analysis, and cutting-edge research in machine learning.
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11 Lesons
21 minutes
On-Demand
Free-Video
TensorFlow

TensorFlow and Deep Reinforcement Learning, Without a PhD - Google I/O '18

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Learn to implement deep reinforcement learning with TensorFlow, teaching a neural network to play Pong using only pixel data. No prior expertise required.
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12 Lesons
41 minutes
On-Demand
Free-Video
Alexander Amini

Introduction to Deep Learning

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Comprehensive introduction to deep learning fundamentals, covering perceptrons, neural networks, loss functions, gradient descent, backpropagation, and regularization techniques.
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15 Lesons
53 minutes
On-Demand
Free-Video
Brandon Rohrer

How Convolutional Neural Networks Work, in Depth

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Comprehensive exploration of convolutional neural networks, covering their structure, operation, and training process, including key concepts like filtering, pooling, and backpropagation.
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24 Lesons
1 hour 1 minute
On-Demand
Free-Video
Institute for Advanced Study

Geodesically Convex Optimization - Can We Prove P!=NP Using Gradient Descent - Avi Wigderson

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Explore geodesically convex optimization and its potential to prove P≠NP using gradient descent in this advanced seminar by renowned mathematician Avi Wigderson.
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12 Lesons
1 hour 58 minutes
On-Demand
Free-Video
Institute for Advanced Study

Fixing GAN Optimization Through Competitive Gradient Descent - Anima Anandkumar

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Explore competitive gradient descent for optimizing GANs, covering strategic equilibria, applications in ML, and numerical results. Gain insights into modeling competing agents and solving GANs.
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20 Lesons
35 minutes
On-Demand
Free-Video
Institute for Advanced Study

A Practical Guide to Deep Learning - Richard Zemel

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Explore deep learning fundamentals, from perceptrons to neural networks, with practical insights on object recognition, vision, and advanced techniques like regularization.
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26 Lesons
2 hours 3 minutes
On-Demand
Free-Video
National Taiwan University

Machine Learning

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從基礎到高級主題的全面機器學習課程,涵蓋回歸、分類、深度學習、無監督學習等,並包含實際演示和案例研究,幫助學習者掌握關鍵概念和技術。
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36 Lesons
1 day 4 hours
On-Demand
Free-Video

PyTorch Tutorials 神经网络 教学

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深入探讨PyTorch神经网络：从基础概念到高级应用，涵盖CNN、RNN、自编码器、强化学习和GAN，并讲解优化技巧如批标准化和过拟合处理。
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35 Lesons
5 hours
On-Demand
Free-Video

모두를 위한 딥러닝 - PyTorch

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PyTorch를 활용한 딥러닝 기초부터 고급 기술까지 실습 중심으로 학습. 텐서 조작, 선형 회귀, CNN, RNN 등 다양한 모델 구현 및 최적화 기법 습득.
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34 Lesons
10 hours
On-Demand
Free-Video

Deep learning ด้วย tensorflow และ keras

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เรียนรู้การสร้างโมเดล Deep Learning ด้วย TensorFlow และ Keras ตั้งแต่พื้นฐานจนถึงระดับสูง ครอบคลุมการติดตั้ง การใช้งาน และเทคนิคการปรับแต่งโมเดล
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46 Lesons
11 hours
On-Demand
Free-Video

TensorFlow Tutorials 神经网络 教学 教程

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从零开始学习TensorFlow构建神经网络，涵盖基础概念、CNN、RNN等高级主题，通过实例和可视化深入理解深度学习原理和应用。
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44 Lesons
7 hours
On-Demand
Free-Video

Formation Tensorflow 2.0

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Apprenez les fondamentaux de TensorFlow 2.0, des perceptrons aux réseaux de neurones récurrents, en passant par la normalisation des données et la création de modèles personnalisés.
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22 Lesons
6 hours
On-Demand
Free-Video
5 Minutes Engineering

Machine Learning and Neural Networks: Cost Function and Gradient Descent - Day 12

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Explore cost functions and gradient descent in machine learning and neural networks, focusing on their role in optimizing model performance and accuracy.
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1 Lesons
32 minutes
On-Demand
Free-Video
Centre International de Rencontres Mathématiques

Curiosities and Counterexamples in Smooth Convex Optimization

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Explore counterexamples and curiosities in smooth convex optimization, focusing on key concepts and unique aspects of this mathematical field.
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1 Lesons
36 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
Simons Institute

Min-Max Optimization - Part I

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Explore min-max optimization, equilibrium computation, and adversarial gradient descent in zero-sum games, connecting classical techniques to deep learning applications.
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10 Lesons
1 hour 3 minutes
On-Demand
Free-Video
Google TechTalks

Differentially Private Online-to-Batch Conversion for Stochastic Optimization

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Explore differentially private stochastic optimization techniques, comparing simple preprocessing and custom algorithms. Learn about a novel online-to-batch conversion method for optimal private convergence rates.
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26 Lesons
50 minutes
On-Demand
Free-Video
Institut des Hautes Etudes Scientifiques (IHES)

Stable Adaptation and Learning in Nonlinear Systems and Neural Networks

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Explore nonlinear systems tools for insights on collective computation and learning in large dynamical networks, focusing on stable adaptation and implicit sparse regularization.
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1 Lesons
35 minutes
On-Demand
Free-Video
Inside Livermore Lab

Rodin: Density and Topology Optimization Framework - MFEM Workshop 2022

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Explore Rodin, a C++17 framework for shape, density, and topology optimization. Learn its functionalities, from refining shapes to solving variational problems in scientific simulations.
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16 Lesons
22 minutes
On-Demand
Free-Video
Yannic Kilcher

I Built a Neural Network in Minecraft - Analog Redstone Network with Backprop and Optimizer (No Mods)

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Explore the creation of an analog neural network in Minecraft using redstone, featuring backpropagation and weight updates. Learn about innovative applications of game mechanics in machine learning.
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8 Lesons
22 minutes
On-Demand
Free-Video
Simons Institute

Yes, Generative Models Are The New Sparsity

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Explore how generative models revolutionize data compression and signal processing, offering new perspectives on sparsity and optimization in machine learning.
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17 Lesons
47 minutes
On-Demand
Free-Video
Institute for Pure & Applied Mathematics (IPAM)

Beyond Lazy Training for Over-parameterized Tensor Decomposition

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Explore tensor decomposition in over-parameterized settings, analyzing gradient descent variants and their performance beyond lazy training regimes for improved optimization in neural networks.
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15 Lesons
29 minutes
On-Demand
Free-Video
Applied Algebraic Topology Network

Differential Calculus on Persistence Barcodes

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Explore differential calculus on persistence barcodes, covering differentiability concepts, lifts to ordered barcodes, and applications in topological data analysis.
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1 Lesons
29 minutes
On-Demand
Free-Video
Weights & Biases

Math for Machine Learning - Exercises: Probability

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Hands-on exercises exploring probability concepts in machine learning, including entropy, cross-entropy, and Gaussian distributions, with practical applications and insights.
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16 Lesons
44 minutes
On-Demand
Free-Video
Institute for Pure & Applied Mathematics (IPAM)

On Quantum Linear Algebra for Machine Learning - IPAM at UCLA

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Explore quantum singular value transformation for machine learning, its applications, limitations, and connections to classical algorithms in this technical talk on quantum linear algebra.
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8 Lesons
35 minutes
On-Demand
Free-Video
International Centre for Theoretical Sciences

Introductory Lectures on First-Order Convex Optimization - Lecture 1

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Explore first-order convex optimization, covering gradient descent, complexity, smoothness, and Nesterov's accelerated algorithm. Gain insights into theoretical foundations and practical applications in machine learning.
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18 Lesons
1 hour 44 minutes
On-Demand
Free-Video
Fields Institute

Beyond Lazy Training for Over-parameterized Tensor Decomposition

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Explore over-parameterization in tensor decomposition, comparing lazy training and gradient descent approaches. Discover how gradient descent can leverage low-rank data structure beyond lazy training regimes.
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17 Lesons
37 minutes
On-Demand
Free-Video
Alan Turing Institute

Can Learning Theory Resist Deep Learning? - Francis Bach, INRIA

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Exploring global convergence of gradient descent in non-convex optimization for deep learning, highlighting challenges in bridging theory and practice in machine learning algorithms.
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19 Lesons
43 minutes
On-Demand
Free-Video
Simons Institute

Optimization: Higher-order Methods - Part 1

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Explore advanced optimization techniques using higher-order methods, focusing on theoretical foundations and practical applications in algorithm design and data structures.
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1 Lesons
57 minutes
On-Demand
Free-Video
Simons Institute

Optimization: First-order Methods - Part 2

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Explore advanced first-order optimization techniques, focusing on accelerated gradient methods and their applications in solving complex algorithmic problems.
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1 Lesons
1 hour 5 minutes
On-Demand
Free-Video
Simons Institute

Optimization: First-order Methods - Part 1

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Explore first-order optimization methods with Alina Ene, focusing on fundamental techniques and algorithms for efficient problem-solving in data structures and algorithm design.
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1 Lesons
57 minutes
On-Demand
Free-Video
Centre International de Rencontres Mathématiques

Geometry and Topology of Spaces of Structured Matrices

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Explore geometric and topological aspects of structured matrices, including momentum maps, frame spaces, and applications in compressed sensing and graph theory.
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12 Lesons
38 minutes
On-Demand
Free-Video
NPTEL-NOC IITM

Maximum Likelihood Estimate for Logistic Regression

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Explore maximum likelihood estimation for logistic regression, covering likelihood functions and gradient descent techniques.
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1 Lesons
10 minutes
On-Demand
Free-Video
Georgia Tech Research

Mathematics for Deep Neural Networks: Energy Landscape and Open Problems - Lecture 5

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Explore the energy landscape of deep neural networks and future challenges in statistical theory, focusing on gradient descent methods and important developments.
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1 Lesons
1 hour 3 minutes
On-Demand
Free-Video
Galileo Galilei Institute

Introduction to the Dynamics of Disordered Systems - Equilibrium and Gradient Descent - Part 3

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Explore equilibrium dynamics and gradient descent in disordered systems, focusing on theoretical concepts and practical applications in statistical physics and optimization.
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1 Lesons
1 hour 36 minutes
On-Demand
Free-Video
Churchill CompSci Talks

A Primer in Machine Learning

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Explore machine learning fundamentals, including hypotheses, data representation, algorithms like regression and classification, and practical implementation using MATLAB.
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14 Lesons
31 minutes
On-Demand
Free-Video
INSAIT Institute

Towards Collaborative Decentralized Learning

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Explore cutting-edge decentralized learning concepts, from federated systems to Byzantine-robust training, with insights into collaborative and personalized optimization approaches.
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13 Lesons
24 minutes
On-Demand
Free-Video
INSAIT Institute

Neurosymbolic Programming - An Emerging Subarea of AI

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Explore neurosymbolic programming's fusion of deep learning and program synthesis, discovering how it enhances AI robustness, interpretability, and efficiency through symbolic and neural approaches.
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1 Lesons
59 minutes
On-Demand
Free-Video
Data Science Conference

Building and Optimization of Neural Networks from Scratch with NumPy

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Master neural network development from ground up using NumPy, covering architecture design, propagation methods, and optimization techniques for building efficient deep learning models without frameworks.
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1 Lesons
1 hour 25 minutes
On-Demand
Free-Video
UofU Data Science

Machine Learning Mid-Semester Review - Lecture 15

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Dive into a comprehensive mid-semester review of fundamental machine learning concepts, covering key principles and techniques explored throughout the academic term.
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1 Lesons
1 hour 21 minutes
On-Demand
Free-Video
UofU Data Science

Machine Learning: Neural Networks and Deep Learning - Lecture 18

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Dive into advanced data science concepts through comprehensive coverage of machine learning principles, algorithms, and practical applications in this university-level lecture.
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1 Lesons
1 hour 20 minutes
On-Demand
Free-Video
UofU Data Science

Machine Learning Fundamentals - Lecture 16

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Dive into advanced data science concepts through comprehensive coverage of machine learning principles, algorithms, and practical applications in this university-level lecture.
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1 Lesons
1 hour 19 minutes
On-Demand
Free-Video
UofU Data Science

Machine Learning Fundamentals - Lecture 15

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Dive into advanced data science concepts through comprehensive coverage of machine learning principles, algorithms, and practical applications in this university-level lecture.
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1 Lesons
1 hour 19 minutes
On-Demand
Free-Video
UofU Data Science

Machine Learning Fundamentals - Lecture 14

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Dive into advanced machine learning concepts and techniques through comprehensive coverage of key algorithms, theoretical foundations, and practical applications in data science.
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1 Lesons
1 hour 19 minutes
On-Demand
Free-Video
UofU Data Science

Machine Learning Fundamentals - Lecture 13

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Dive into advanced machine learning concepts and techniques through comprehensive coverage of key algorithms, theoretical foundations, and practical applications in data science.
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1 Lesons
1 hour 21 minutes
On-Demand
Free-Video
UofU Data Science

Machine Learning Fundamentals - Lecture 12

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Dive into advanced machine learning concepts and data science fundamentals through comprehensive theoretical discussions and practical applications in this graduate-level lecture.
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1 Lesons
1 hour 18 minutes
On-Demand
Free-Video
UofU Data Science

Machine Learning Fundamentals - Lecture 11

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Dive into advanced machine learning concepts and data science fundamentals through comprehensive theoretical discussions and practical applications at a graduate level.
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1 Lesons
1 hour 20 minutes
On-Demand
Free-Video
UofU Data Science

Machine Learning: Neural Networks and Deep Learning - Lecture 22

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Dive into advanced data science concepts through comprehensive coverage of machine learning principles, algorithms, and practical applications in this graduate-level academic lecture.
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1 Lesons
1 hour 20 minutes
On-Demand
Free-Video
UofU Data Science

Machine Learning: Neural Networks and Deep Learning - Lecture 21

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Dive into advanced data science concepts through comprehensive coverage of machine learning principles, algorithms, and practical applications in this graduate-level academic lecture.
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1 Lesons
1 hour 20 minutes
On-Demand
Free-Video
UofU Data Science

Machine Learning - Lecture 20

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Dive into advanced data science concepts through comprehensive coverage of machine learning principles, algorithms, and practical applications in this university-level lecture.
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1 Lesons
1 hour 16 minutes
On-Demand
Free-Video
UofU Data Science

Machine Learning - Lecture 19

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Dive into advanced data science concepts through comprehensive coverage of machine learning principles, algorithms, and practical applications in this university-level lecture.
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1 Lesons
1 hour 14 minutes
On-Demand
Free-Video
UofU Data Science

Neural Networks and Backpropagation Algorithm - Lecture 27

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Dive into the backpropagation algorithm and advanced neural network concepts, mastering fundamental techniques for training deep learning models effectively.
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1 Lesons
1 hour 20 minutes
On-Demand
Free-Video
UofU Data Science

Introduction to Neural Networks - Lecture 25

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Explore neural networks' fundamental concepts, structure, and prediction mechanisms while learning essential training approaches for building effective machine learning models.
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1 Lesons
1 hour 21 minutes
On-Demand
Free-Video
Data Science Courses

Recurrent Neural Networks and Backpropagation Through Time - Lecture 8

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Dive into recurrent neural networks, exploring LSTM, GRU architectures, and advanced concepts like backpropagation through time and gradient challenges in deep learning implementations.
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1 Lesons
1 hour 15 minutes
On-Demand
Free-Video
Squid: Schools for Quantum Information Development

Trained Quantum Neural Networks are Gaussian Processes

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Explore the mathematical foundations of quantum neural networks, focusing on their convergence to Gaussian processes and implications for training in supervised learning scenarios.
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1 Lesons
25 minutes
On-Demand
Free-Video
Centre for Networked Intelligence, IISc

Cost-Efficient Distributed Learning

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Discover strategies for optimizing distributed gradient descent algorithms by managing worker responses and implementing adaptive techniques to balance computational efficiency with model quality in machine learning systems.
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1 Lesons
1 hour 3 minutes
On-Demand
Free-Video
UofU Data Science

Neural Networks and Backpropagation - Lecture 26

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Dive into neural network training fundamentals through backpropagation, learning essential parameter optimization techniques and mathematical foundations for deep learning implementation.
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1 Lesons
1 hour 19 minutes
On-Demand
Free-Video
UofU Data Science

Machine Learning Foundations - Logistic Regression

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Master logistic regression fundamentals through hands-on practice, exploring core concepts, implementation techniques, and practical applications in machine learning and data analysis.
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1 Lesons
1 hour 19 minutes
On-Demand
Free-Video
UofU Data Science

Practical Issues with Neural Networks in Machine Learning - Lecture 27

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Explore practical challenges and solutions for training large neural networks, including effective strategies and optimization techniques for improved performance.
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1 Lesons
1 hour 7 minutes
On-Demand
Free-Video
UofU Data Science

Neural Networks Foundations - Feedforward Neural Networks

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Master the fundamentals of feedforward neural networks, exploring their architecture, functionality, and implementation principles for building effective machine learning models.
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1 Lesons
1 hour 20 minutes
On-Demand
Free-Video
UofU Data Science

Machine Learning - Lecture 28

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Dive into advanced data science concepts through comprehensive coverage of machine learning principles, algorithms, and practical applications in this graduate-level lecture from University of Utah.
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1 Lesons
1 hour 21 minutes
On-Demand
Free-Video
UofU Data Science

Machine Learning: Neural Networks and Deep Learning - Lecture 27

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Dive into advanced data science concepts through comprehensive coverage of machine learning principles, algorithms, and practical applications in this graduate-level lecture from University of Utah.
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1 Lesons
1 hour 15 minutes
On-Demand
Free-Video
UofU Data Science

PyTorch Tutorial for Machine Learning - Fall 2023

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Master PyTorch fundamentals and essential deep learning concepts through hands-on practice with neural networks, tensors, and gradient-based optimization techniques.
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1 Lesons
36 minutes
On-Demand
Free-Video
UofU Data Science

Introduction to Neural Networks: Classification, Softmax, and Training Techniques

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Master the fundamentals of neural networks, from nonlinear and multiclass classification to feedforward networks, training techniques, and optimization strategies for improved model performance.
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7 Lesons
1 hour 19 minutes
On-Demand
Free-Video
UofU Data Science

Machine Learning - Lecture 25

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Dive into advanced data science concepts through comprehensive coverage of machine learning principles, algorithms, and practical applications in this graduate-level lecture from University of Utah.
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1 Lesons
1 hour 11 minutes
On-Demand
Free-Video
UofU Data Science

Machine Learning - Lecture 24

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Dive into advanced data science concepts through comprehensive coverage of machine learning principles, algorithms, and practical applications in this graduate-level lecture from University of Utah.
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1 Lesons
1 hour 11 minutes
On-Demand
Free-Video
UofU Data Science

Machine Learning - Lecture 23

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Dive into advanced data science concepts through comprehensive coverage of machine learning principles, algorithms, and practical applications in this graduate-level academic lecture.
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1 Lesons
1 hour 20 minutes
On-Demand
Free-Video
The Full Stack

Deep Learning Fundamentals - Full Stack Deep Learning

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Comprehensive overview of deep learning basics, covering neural networks, learning problems, optimization techniques, and architectural considerations for AI practitioners.
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9 Lesons
30 minutes
On-Demand
Free-Video
USC Probability and Statistics Seminar

Rank Overparameterization and Global Optimality Certification in Low-Rank Matrix Estimation

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Explore rank overparameterization in nonconvex optimization, its impact on spurious local minima, and methods for certifying global optimality in large-scale problems.
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1 Lesons
52 minutes
On-Demand
Free-Video
ACM SIGPLAN

Automatic Differentiation - Session Preview at POPL 2023

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Explore automatic differentiation techniques and their applications in programming languages, presented by expert Sasa Misailovic at POPL 2023.
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1 Lesons
10 minutes
On-Demand
Free-Video
AutoML Seminars

Gradient Descent: The Ultimate Optimizer - Automating Hyperparameter Optimization

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Discover how to automatically optimize hyperparameters in gradient-based ML algorithms through an elegant modification to backpropagation, making optimizer tuning more efficient and less sensitive to initial choices.
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1 Lesons
30 minutes
On-Demand
Free-Video
Aleksa Gordić - The AI Epiphany

Machine Learning with JAX - From Hero to HeroPro+

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Advanced JAX tutorial covering PyTrees, parallelism, multi-device training, and advanced techniques for efficient machine learning model implementation and training.
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12 Lesons
1 hour 9 minutes
On-Demand
Free-Video
Computerphile

Generative Adversarial Networks - Computerphile

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Explore Generative Adversarial Networks (GANs) with Rob Miles, learning how neural networks compete to create new, realistic data like images and faces.
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14 Lesons
21 minutes
On-Demand
Free-Video
Sebastian Lague

How to Create a Neural Network and Train It to Identify Doodles

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Comprehensive guide to building and training neural networks from scratch, covering key concepts and practical implementation for image recognition tasks.
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21 Lesons
55 minutes
On-Demand
Free-Video
StatQuest with Josh Starmer

Gradient Boost Part 2 - Regression Details

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Detailed exploration of Gradient Boost algorithm for regression, covering initialization, tree building, residual calculation, and prediction optimization. Ideal for those seeking in-depth understanding of this popular machine learning technique.
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15 Lesons
27 minutes
On-Demand
Free-Video
StatQuest with Josh Starmer

Gradient Descent, Step-by-Step

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Comprehensive step-by-step explanation of Gradient Descent, covering its application in Machine Learning, optimization techniques, and variations like Stochastic Gradient Descent.
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10 Lesons
24 minutes
On-Demand
Free-Video
Society for Industrial and Applied Mathematics

Optimization, Complexity and Math - Can We Prove P!=NP by Gradient Descent?

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Explore optimization, complexity, and mathematics with Avi Wigderson. Delve into perfect matchings, symbolic matrices, and operator scaling, connecting diverse areas of mathematics and computer science.
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11 Lesons
55 minutes
On-Demand
Free-Video
International Centre for Theoretical Sciences

Differentiable Programming for End-to-end Optimization of Experiments - Lecture 6

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Explore differentiable programming for optimizing experiments in high-energy physics, focusing on end-to-end solutions and advanced machine learning techniques.
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1 Lesons
2 hours 6 minutes
On-Demand
Free-Video
Nicholas Renotte

Building the Gradient Descent Algorithm - Coding Challenge

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Hands-on tutorial for building a gradient descent algorithm from scratch in Python, implementing a regression machine learning model using only NumPy.
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7 Lesons
22 minutes
On-Demand
Free-Video