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📐 ML Fundamentals

Neural networks, backpropagation, gradient descent — the maths behind AI

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Intel: How Google Health Uses Machine Learning With Intel
ML Fundamentals ⚡ AI Lesson
Intel: How Google Health Uses Machine Learning With Intel
The New Stack Beginner 5y ago
L4.5 A Fully Connected (Linear) Layer in PyTorch
ML Fundamentals
L4.5 A Fully Connected (Linear) Layer in PyTorch
Sebastian Raschka Beginner 5y ago
L4.4 Notational Conventions for Neural Networks
ML Fundamentals
L4.4 Notational Conventions for Neural Networks
Sebastian Raschka Beginner 5y ago
What the Heck is Bayesian Stats ?? : Data Science Basics
ML Fundamentals
What the Heck is Bayesian Stats ?? : Data Science Basics
ritvikmath Beginner 5y ago
How does a Data Scientist Fight FRAUD?
ML Fundamentals ⚡ AI Lesson
How does a Data Scientist Fight FRAUD?
CodeEmporium Beginner 5y ago
Push Notifications from Jupyter Notebook after Code Execution [Python for Data Science]
ML Fundamentals
Push Notifications from Jupyter Notebook after Code Execution [Python for Data Science]
1littlecoder Beginner 5y ago
The SoftMax Derivative, Step-by-Step!!!
ML Fundamentals
The SoftMax Derivative, Step-by-Step!!!
StatQuest with Josh Starmer Beginner 5y ago
Neural Networks Part 5: ArgMax and SoftMax
ML Fundamentals
Neural Networks Part 5: ArgMax and SoftMax
StatQuest with Josh Starmer Beginner 5y ago
Simple Explanation of LSTM | Deep Learning Tutorial 36 (Tensorflow, Keras & Python)
ML Fundamentals ⚡ AI Lesson
Simple Explanation of LSTM | Deep Learning Tutorial 36 (Tensorflow, Keras & Python)
codebasics Beginner 5y ago
Build a 1D convolutional neural network, part 7: Evaluate the model
ML Fundamentals
Build a 1D convolutional neural network, part 7: Evaluate the model
Brandon Rohrer Beginner 5y ago
Build a 1D convolutional neural network, part 6: Text summary and loss history
ML Fundamentals
Build a 1D convolutional neural network, part 6: Text summary and loss history
Brandon Rohrer Beginner 5y ago
Run Jupyter Lab for Python, R, Swift from Google Colab with ColabCode
ML Fundamentals
Run Jupyter Lab for Python, R, Swift from Google Colab with ColabCode
1littlecoder Beginner 5y ago
Rosanne Liu — Conducting Fundamental ML Research as a Nonprofit
ML Fundamentals
Rosanne Liu — Conducting Fundamental ML Research as a Nonprofit
Weights & Biases Beginner 5y ago
Deep Networks Are Kernel Machines (Paper Explained)
ML Fundamentals
Deep Networks Are Kernel Machines (Paper Explained)
Yannic Kilcher Beginner 5y ago
Let's talk about AGI: Elon Musk vs Andrew Ng on Superintelligence
ML Fundamentals
Let's talk about AGI: Elon Musk vs Andrew Ng on Superintelligence
Aladdin Persson Beginner 5y ago
Capturing Object Detection History with Tensorflow Object Detection and Python
ML Fundamentals
Capturing Object Detection History with Tensorflow Object Detection and Python
Nicholas Renotte Beginner 5y ago
This Neural Network Makes Virtual Humans Dance! 🕺
ML Fundamentals
This Neural Network Makes Virtual Humans Dance! 🕺
Two Minute Papers Beginner 5y ago
Predicting Stock Prices in Python
ML Fundamentals ⚡ AI Lesson
Predicting Stock Prices in Python
NeuralNine Beginner 5y ago
A Future of Work for the Invisible Workers in A.I. with Saiph Savage - #447
ML Fundamentals ⚡ AI Lesson
A Future of Work for the Invisible Workers in A.I. with Saiph Savage - #447
The TWIML AI Podcast with Sam Charrington Beginner 5y ago
The Importance and Concern of NLP in National Intelligence with Sean Gourley, Primer CEO
ML Fundamentals
The Importance and Concern of NLP in National Intelligence with Sean Gourley, Primer CEO
Weights & Biases Beginner 5y ago
15 Programming Project Ideas - From Beginner to Advanced
ML Fundamentals
15 Programming Project Ideas - From Beginner to Advanced
Tech With Tim Beginner 5y ago
L4.3 Vectors, Matrices, and Broadcasting
ML Fundamentals
L4.3 Vectors, Matrices, and Broadcasting
Sebastian Raschka Beginner 5y ago
L4.2 Tensors in PyTorch
ML Fundamentals
L4.2 Tensors in PyTorch
Sebastian Raschka Beginner 5y ago
L4.1 Tensors in Deep Learning
ML Fundamentals
L4.1 Tensors in Deep Learning
Sebastian Raschka Beginner 5y ago
L4.0 Linear Algebra for Deep Learning -- Lecture Overview
ML Fundamentals
L4.0 Linear Algebra for Deep Learning -- Lecture Overview
Sebastian Raschka Beginner 5y ago
Build a 1D convolutional neural network, part 5: One Hot, Flatten, and Logging blocks
ML Fundamentals
Build a 1D convolutional neural network, part 5: One Hot, Flatten, and Logging blocks
Brandon Rohrer Beginner 5y ago
Build a 1D convolutional neural network , part 3: Connect the blocks into a network structure
ML Fundamentals
Build a 1D convolutional neural network , part 3: Connect the blocks into a network structure
Brandon Rohrer Beginner 5y ago
Build a 1D convolutional neural network , part 2: Collect the Cottonwood blocks
ML Fundamentals ⚡ AI Lesson
Build a 1D convolutional neural network , part 2: Collect the Cottonwood blocks
Brandon Rohrer Beginner 5y ago
Build a 1D convolutional neural network, part 1: Create a test data set
ML Fundamentals
Build a 1D convolutional neural network, part 1: Create a test data set
Brandon Rohrer Beginner 5y ago
Implement 1D convolution, part 7: Weight gradient and input gradient
ML Fundamentals
Implement 1D convolution, part 7: Weight gradient and input gradient
Brandon Rohrer Beginner 5y ago
Implement 1D convolution, part 6: Multi-channel, multi-kernel convolutions
ML Fundamentals
Implement 1D convolution, part 6: Multi-channel, multi-kernel convolutions
Brandon Rohrer Beginner 5y ago
Implement 1D convolution, part 5: Forward and backward pass
ML Fundamentals ⚡ AI Lesson
Implement 1D convolution, part 5: Forward and backward pass
Brandon Rohrer Beginner 5y ago
Implement 1D convolution, part 4: Initialize the convolution block
ML Fundamentals ⚡ AI Lesson
Implement 1D convolution, part 4: Initialize the convolution block
Brandon Rohrer Beginner 5y ago
Implement 1D convolution, part 3: Create the convolution block
ML Fundamentals
Implement 1D convolution, part 3: Create the convolution block
Brandon Rohrer Beginner 5y ago
Implement 1D convolution, part 2: Comparison with NumPy convolution()
ML Fundamentals
Implement 1D convolution, part 2: Comparison with NumPy convolution()
Brandon Rohrer Beginner 5y ago
L3.1 About Brains and Neurons
ML Fundamentals
L3.1 About Brains and Neurons
Sebastian Raschka Beginner 5y ago
L3.5 The Geometric Intuition Behind the Perceptron
ML Fundamentals
L3.5 The Geometric Intuition Behind the Perceptron
Sebastian Raschka Beginner 5y ago
L3.3 Vectorization in Python
ML Fundamentals
L3.3 Vectorization in Python
Sebastian Raschka Beginner 5y ago
L3.4 Perceptron in Python using NumPy and PyTorch
ML Fundamentals
L3.4 Perceptron in Python using NumPy and PyTorch
Sebastian Raschka Beginner 5y ago
L3.2 The Perceptron Learning Rule
ML Fundamentals
L3.2 The Perceptron Learning Rule
Sebastian Raschka Beginner 5y ago
L3.0 Perceptron Lecture Overview
ML Fundamentals
L3.0 Perceptron Lecture Overview
Sebastian Raschka Beginner 5y ago
L2.4 The Deep Learning Hardware & Software Landscape
ML Fundamentals
L2.4 The Deep Learning Hardware & Software Landscape
Sebastian Raschka Beginner 5y ago
L2.3 The Origins of Deep Learning
ML Fundamentals
L2.3 The Origins of Deep Learning
Sebastian Raschka Beginner 5y ago
L2.1 Artificial Neurons
ML Fundamentals
L2.1 Artificial Neurons
Sebastian Raschka Beginner 5y ago
L2.2 Multilayer Networks
ML Fundamentals
L2.2 Multilayer Networks
Sebastian Raschka Beginner 5y ago
L2.0 A Brief History of Deep Learning -- Lecture Overview
ML Fundamentals
L2.0 A Brief History of Deep Learning -- Lecture Overview
Sebastian Raschka Beginner 5y ago
L1.6 About the Practical Aspects and Tools Used in This Course
ML Fundamentals
L1.6 About the Practical Aspects and Tools Used in This Course
Sebastian Raschka Beginner 5y ago
L1.5 Necessary Machine Learning Notation and Jargon
ML Fundamentals
L1.5 Necessary Machine Learning Notation and Jargon
Sebastian Raschka Beginner 5y ago
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Introduction to Deep Learning & Neural Networks with Keras
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Introduction to Deep Learning & Neural Networks with Keras
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VLSI CAD Part II: Layout
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VLSI CAD Part II: Layout
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AI & Quantum Computing – Zero to Expert Bootcamp
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AI & Quantum Computing – Zero to Expert Bootcamp
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Evaluate Vision Errors: Identify Failure Patterns
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Evaluate Vision Errors: Identify Failure Patterns
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Creating Multi Task Models With Keras
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Creating Multi Task Models With Keras
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Core Machine Learning & Evaluation
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Core Machine Learning & Evaluation
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