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📐 ML Fundamentals

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

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L10.5.1 The Main Concept Behind Dropout
ML Fundamentals
L10.5.1 The Main Concept Behind Dropout
Sebastian Raschka Intermediate 5y ago
L10.3 Early Stopping
ML Fundamentals
L10.3 Early Stopping
Sebastian Raschka Intermediate 5y ago
Live AWS For Data Science - Deploying Machine Learning Application In EC2 Instance
ML Fundamentals
Live AWS For Data Science - Deploying Machine Learning Application In EC2 Instance
Krish Naik Intermediate 5y ago
Radial Basis Function Kernel : Data Science Concepts
ML Fundamentals
Radial Basis Function Kernel : Data Science Concepts
ritvikmath Intermediate 5y ago
Monday Night Live Q&A - Ask Anything Related To Data Science
ML Fundamentals
Monday Night Live Q&A - Ask Anything Related To Data Science
Krish Naik Intermediate 5y ago
Metric Learning for Images - Keras Code Examples
ML Fundamentals
Metric Learning for Images - Keras Code Examples
Connor Shorten Intermediate 5y ago
Expert Panel: Optimizing BizOps with AI
ML Fundamentals
Expert Panel: Optimizing BizOps with AI
DeepLearningAI Intermediate 5y ago
SVM Kernels : Data Science Concepts
ML Fundamentals
SVM Kernels : Data Science Concepts
ritvikmath Intermediate 5y ago
Speech Command Recognition With Tensorflow.JS and React.JS | Javascript AI
ML Fundamentals
Speech Command Recognition With Tensorflow.JS and React.JS | Javascript AI
Nicholas Renotte Intermediate 5y ago
Democratize AI with OneAPI
ML Fundamentals
Democratize AI with OneAPI
The New Stack Intermediate 5y ago
Building a recommendation system using deep learning
ML Fundamentals
Building a recommendation system using deep learning
Abhishek Thakur Intermediate 5y ago
Build a 2D convolutional neural network, part 17: Cottonwood cheatsheet
ML Fundamentals
Build a 2D convolutional neural network, part 17: Cottonwood cheatsheet
Brandon Rohrer Intermediate 5y ago
Build a 2D convolutional neural network, part 16: Cottonwood code tour
ML Fundamentals
Build a 2D convolutional neural network, part 16: Cottonwood code tour
Brandon Rohrer Intermediate 5y ago
Career Advice Office Hours - Job Applications | Coursera
ML Fundamentals
Career Advice Office Hours - Job Applications | Coursera
Coursera Intermediate 5y ago
He got 5 internships and 2 job offers | Interview with Zomato machine learning engineer
ML Fundamentals
He got 5 internships and 2 job offers | Interview with Zomato machine learning engineer
codebasics Intermediate 5y ago
How I hacked my Nest camera to run custom models
ML Fundamentals
How I hacked my Nest camera to run custom models
Roboflow Intermediate 5y ago
Do this to get a data science job abroad
ML Fundamentals
Do this to get a data science job abroad
codebasics Intermediate 5y ago
RandAugment Paper Walkthrough
ML Fundamentals
RandAugment Paper Walkthrough
Aladdin Persson Intermediate 5y ago
Q&A + Giveaway for 10 Years on YouTube
ML Fundamentals
Q&A + Giveaway for 10 Years on YouTube
Veritasium Intermediate 5y ago
L10.1 Techniques for Reducing Overfitting
ML Fundamentals
L10.1 Techniques for Reducing Overfitting
Sebastian Raschka Intermediate 5y ago
PerceptiLabs-The Best Machine Learning Visual Modeling Tool-Train Deep Learning Neural Network
ML Fundamentals
PerceptiLabs-The Best Machine Learning Visual Modeling Tool-Train Deep Learning Neural Network
Krish Naik Intermediate 5y ago
Session On Different Types Of Loss Function In Deep Learning
ML Fundamentals
Session On Different Types Of Loss Function In Deep Learning
Krish Naik Intermediate 5y ago
Coding MCMC : Data Science Code
ML Fundamentals
Coding MCMC : Data Science Code
ritvikmath Intermediate 5y ago
Sunday Late Night Live Q&A - Ask Anything Related To Data Science
ML Fundamentals
Sunday Late Night Live Q&A - Ask Anything Related To Data Science
Krish Naik Intermediate 5y ago
Bayesian Treasure Hunt : Data Science Code
ML Fundamentals
Bayesian Treasure Hunt : Data Science Code
ritvikmath Intermediate 5y ago
Deep Learning News #2, Feb 6 2021
ML Fundamentals
Deep Learning News #2, Feb 6 2021
Sebastian Raschka Intermediate 5y ago
Build a 2D convolutional neural network, part 15: Rendering examples
ML Fundamentals
Build a 2D convolutional neural network, part 15: Rendering examples
Brandon Rohrer Intermediate 5y ago
Build a 2D convolutional neural network, part 14: Collecting examples
ML Fundamentals
Build a 2D convolutional neural network, part 14: Collecting examples
Brandon Rohrer Intermediate 5y ago
Build a 2D convolutional neural network, part 13: Loss history and text summary
ML Fundamentals
Build a 2D convolutional neural network, part 13: Loss history and text summary
Brandon Rohrer Intermediate 5y ago
Build a 2D convolutional neural network, part 12: Testing loop
ML Fundamentals
Build a 2D convolutional neural network, part 12: Testing loop
Brandon Rohrer Intermediate 5y ago
Build a 2D convolutional neural network, part 11: The training loop
ML Fundamentals
Build a 2D convolutional neural network, part 11: The training loop
Brandon Rohrer Intermediate 5y ago
Build a 2D convolutional neural network, part 10: Connecting layers
ML Fundamentals
Build a 2D convolutional neural network, part 10: Connecting layers
Brandon Rohrer Intermediate 5y ago
Build a 2D convolutional neural network, part 9: Adding layers
ML Fundamentals
Build a 2D convolutional neural network, part 9: Adding layers
Brandon Rohrer Intermediate 5y ago
Build a 2D convolutional neural network, part 8: Training code setup
ML Fundamentals
Build a 2D convolutional neural network, part 8: Training code setup
Brandon Rohrer Intermediate 5y ago
Build a 2D convolutional neural network, part 7: Why Cottonwood?
ML Fundamentals
Build a 2D convolutional neural network, part 7: Why Cottonwood?
Brandon Rohrer Intermediate 5y ago
Build a 2D convolutional neural network, part 6: Examples of successes and failures
ML Fundamentals
Build a 2D convolutional neural network, part 6: Examples of successes and failures
Brandon Rohrer Intermediate 5y ago
Build a 2D convolutional neural network, part 5: Pre-trained model results
ML Fundamentals
Build a 2D convolutional neural network, part 5: Pre-trained model results
Brandon Rohrer Intermediate 5y ago
Build a 2D convolutional neural network, part 4: Model overview
ML Fundamentals
Build a 2D convolutional neural network, part 4: Model overview
Brandon Rohrer Intermediate 5y ago
Build a 2D convolutional neural network, part 3: MNIST digits
ML Fundamentals
Build a 2D convolutional neural network, part 3: MNIST digits
Brandon Rohrer Intermediate 5y ago
Build a 2D convolutional neural network, part 2: Overview
ML Fundamentals
Build a 2D convolutional neural network, part 2: Overview
Brandon Rohrer Intermediate 5y ago
Build a 2D convolutional neural network, part 1: Getting started
ML Fundamentals
Build a 2D convolutional neural network, part 1: Getting started
Brandon Rohrer Intermediate 5y ago
Object Localization Vs Object Detection Deep Learning
ML Fundamentals
Object Localization Vs Object Detection Deep Learning
Krish Naik Intermediate 5y ago
How To Implement Image Classification Using SVM In Convolution Neural Network
ML Fundamentals
How To Implement Image Classification Using SVM In Convolution Neural Network
Krish Naik Intermediate 5y ago
Markov Chain Monte Carlo (MCMC) : Data Science Concepts
ML Fundamentals
Markov Chain Monte Carlo (MCMC) : Data Science Concepts
ritvikmath Intermediate 5y ago
First Live Q&A Of 2021 - Ask Anything Related To Data Science
ML Fundamentals
First Live Q&A Of 2021 - Ask Anything Related To Data Science
Krish Naik Intermediate 5y ago
Papers With Code: The Latest in Machine Learning, Deep Learning And AI
ML Fundamentals
Papers With Code: The Latest in Machine Learning, Deep Learning And AI
Krish Naik Intermediate 5y ago
Accept-Reject Sampling : Data Science Concepts
ML Fundamentals
Accept-Reject Sampling : Data Science Concepts
ritvikmath Intermediate 5y ago
Code With Me : Monte Carlo Method (My First Real-Time Coding Video!)
ML Fundamentals
Code With Me : Monte Carlo Method (My First Real-Time Coding Video!)
ritvikmath Intermediate 5y ago
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Smart Analytics, Machine Learning, and AI on GCP en Español
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Smart Analytics, Machine Learning, and AI on GCP en Español
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Custom and Distributed Training with TensorFlow
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Custom and Distributed Training with TensorFlow
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Introduction to Digital health
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Introduction to Digital health
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Natural Language Processing with Sequence Models
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Natural Language Processing with Sequence Models
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Solving ML Regression Problems with AWS AutoGluon
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Solving ML Regression Problems with AWS AutoGluon
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Machine Learning with Small Data Part 2
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Machine Learning with Small Data Part 2
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