Heart Of Ai - A Theoretical Odyssey On Machine Learning

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Heart Of Ai - A Theoretical Odyssey On Machine Learning (Size: 1.5 GB)
  1 - Course Structure.mp4 30.1 MB
  1 - L2 Norms exercise.html 102.4 B
  10 - QR Decomposition and GramSchmid Process.mp4 47.7 MB
  11 - Basics of Calculus Derivatives and Partial Derivatives.mp4 40.5 MB
  12 - Gradients and Directional Derivatives.mp4 27.8 MB
  13 - Integration Double Triple integrals.mp4 40.5 MB
  14 - Local And Global MinimaMaxima.mp4 37.3 MB
  15 - Gradient Descent And Stochastic Gradient Descent.mp4 45.1 MB
  16 - Newtons Method And Conjugate Gradient Descent.mp4 26.1 MB
  17 - Regularization Techniques L1 L2 Elastic Net.mp4 29 MB
  18 - Random Variables and Probability Distributions.mp4 37 MB
  19 - Joint Marginal and Conditional Distribution.mp4 39.7 MB
  2 - Derivatives Quiz.html 0 B
  2 - Vectors and Matrices Scalar Vector Matrix Tensor.mp4 23.7 MB
  20 - Hypothesis Testing.mp4 32.5 MB
  21 - Confidence Intervals.mp4 27.2 MB
  22 - Maximum Likelihood Estimation MLE and Bayesian Estimation.mp4 36.5 MB
  23 - Naive Bayes Classifier.mp4 26.3 MB
  24 - Gaussian Mixture Models GMMs.mp4 23.3 MB
  25 - Hidden Markov Models HMMs.mp4 23.2 MB
  26 - Jacobian Matrices.mp4 25.4 MB
  27 - Chain Rule and HighOrder Derivatives.mp4 24.3 MB
  28 - Hessian Matrix and secondorder Conditions.mp4 25.4 MB
  29 - Backpropagation in Neural Network.mp4 32.3 MB
  3 - Integration.html 0 B
  3 - Vector Operations.mp4 30.5 MB
  30 - Vanishing And Exploding Gradients.mp4 45.2 MB
  31 - Optimizers Adam RMSProp SGD.mp4 16.8 MB
  32 - Least Square Estimation.mp4 34.9 MB
  33 - Normal Equations and Matrix Formulations.mp4 22.7 MB
  34 - Polynomial Regression.mp4 23.8 MB
  35 - Shannon Entropy.mp4 19.1 MB
  36 - CrossEntropy Loss.mp4 25 MB
  37 - Kullback Leibler Divergence.mp4 22.7 MB
  38 - FeedForward Neural Networks FNNs.mp4 27.3 MB
  39 - Convolutional Neural Networks CNNs.mp4 25.2 MB
  4 - Bayes Theorem.html 0 B
  4 - Matrix Operations.mp4 45.5 MB
  40 - Recurrent Neural Network RNN.mp4 27.7 MB
  41 - Graph Theory And NN.mp4 30.7 MB
  42 - Autoencoders and Variational Autoencoders.mp4 31.1 MB
  43 - Generative Adversarial Networks GANs.mp4 24.1 MB
  44 - Image Classification and Object Detection.mp4 38.7 MB
  45 - Natural Language Processing NLP.mp4 37.3 MB
  46 - Reinforcement Learning.mp4 25.6 MB
  47 - Quantum Machine Learning.mp4 26.5 MB
  48 - PresentationAI.pdf 7.1 MB
  48 - Resources and Further Learning.mp4 31.9 MB
  5 - Norms in ML.mp4 59.1 MB
  6 - Linear Map And Linear Transformation.mp4 57.5 MB
  7 - Eigenvalues and Eigenvectors.mp4 36.4 MB
  8 - Principal Component Analysis.mp4 32 MB
  9 - LU Decomposition.mp4 52.7 MB
  Bonus Resources.txt 409.6 B
  Get Bonus Downloads Here.url 204.8 B
  ▲ 55 total files

Description


Heart Of Ai: A Theoretical Odyssey On Machine Learning
https://FreeCourseWeb.com

Published 9/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.52 GB | Duration: 3h 58m

Unveiling the Elegance of Machine/Deep Learning

What you'll learn
Foundational Understanding of Mathematical Concepts in Machine Learning
Application of Mathematics to Neural Networks
Math-Driven Problem Solving in Deep Learning
Advanced Optimization and Regularization Techniques

Requirements
Basic understanding of algebra, including equations, functions, and basic operations.
Familiarity with basic concepts of calculus, including limits, derivatives, and integrals.
Basic knowledge of probability and statistics, including concepts of probability distributions, mean, and variance.
Basic programming skills in a language like Python, including variables, loops, and functions.
Basic knowledge of machine learning concepts, such as supervised and unsupervised learning.

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