📐 ML Fundamentals

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

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Your GitHub story in 3D- View a 3D Model of your GitHub Contribution graph.

ML Fundamentals

Your GitHub story in 3D- View a 3D Model of your GitHub Contribution graph.

Krish Naik Intermediate 4y ago

Decision and Classification Trees, Clearly Explained!!!

ML Fundamentals ⚡ AI Lesson

Decision and Classification Trees, Clearly Explained!!!

StatQuest with Josh Starmer Beginner 4y ago

Sunday Live Q&A Ask Anything Related Data Science

ML Fundamentals

Sunday Live Q&A Ask Anything Related Data Science

Krish Naik Intermediate 4y ago

Text Generation without Deep Learning - Markov Chain in Python

ML Fundamentals

Text Generation without Deep Learning - Markov Chain in Python

1littlecoder Beginner 4y ago

Detect Duplicate Images in Python with CNN using imagededup | Kaggle Notebook

ML Fundamentals

Detect Duplicate Images in Python with CNN using imagededup | Kaggle Notebook

1littlecoder Beginner 4y ago

Luigi in Production Part 2 // Luigi Patruno // MLOps Coffee Sessions #36

ML Fundamentals

Luigi in Production Part 2 // Luigi Patruno // MLOps Coffee Sessions #36

MLOps.community Beginner 5y ago

Train and Debug YOLOv5 Models with Weights & Biases Integration | YOLOv5 Series Part 0

ML Fundamentals

Train and Debug YOLOv5 Models with Weights & Biases Integration | YOLOv5 Series Part 0

Weights & Biases Beginner 5y ago

L18.4: A GAN for Generating Handwritten Digits in PyTorch -- Code Example

ML Fundamentals

L18.4: A GAN for Generating Handwritten Digits in PyTorch -- Code Example

Sebastian Raschka Beginner 5y ago

L18.3: Modifying the GAN Loss Function for Practical Use

ML Fundamentals

L18.3: Modifying the GAN Loss Function for Practical Use

Sebastian Raschka Beginner 5y ago

Natural Language Processing (NLP) and Text Classification With Python

ML Fundamentals

Natural Language Processing (NLP) and Text Classification With Python

Real Python Beginner 5y ago

Adrien Gaidon — Advancing ML Research in Autonomous Vehicles

ML Fundamentals

Adrien Gaidon — Advancing ML Research in Autonomous Vehicles

Weights & Biases Beginner 5y ago

Advanced Developer Workloads with Built-In AI Acceleration

ML Fundamentals ⚡ AI Lesson

Advanced Developer Workloads with Built-In AI Acceleration

The New Stack Advanced 5y ago

Backpropagation : Data Science Concepts

ML Fundamentals ⚡ AI Lesson

Backpropagation : Data Science Concepts

ritvikmath Beginner 5y ago

MLOps Community 1 Year Anniversary! // Meetup #59 clip

ML Fundamentals

MLOps Community 1 Year Anniversary! // Meetup #59 clip

MLOps.community Beginner 5y ago

Node-Red: Visual coding for ML on Raspberry Pi and beyond - Made with TensorFlow.js

ML Fundamentals ⚡ AI Lesson

Node-Red: Visual coding for ML on Raspberry Pi and beyond - Made with TensorFlow.js

TensorFlow Beginner 5y ago

Intro to Neural Networks : Data Science Concepts

ML Fundamentals ⚡ AI Lesson

Intro to Neural Networks : Data Science Concepts

ritvikmath Beginner 5y ago

1. Live coding Jarvis Transcriptions for Speech to Text Dataset p.1

ML Fundamentals

1. Live coding Jarvis Transcriptions for Speech to Text Dataset p.1

sentdex Beginner 5y ago

Preprocessing data for Machine Learning - Deep Dive

ML Fundamentals ⚡ AI Lesson

Preprocessing data for Machine Learning - Deep Dive

CodeEmporium Beginner 5y ago

Flesch Kincaid Readability Tests

ML Fundamentals ⚡ AI Lesson

Flesch Kincaid Readability Tests

Data Skeptic Beginner 5y ago

Multiclass logistic/softmax regression from scratch

ML Fundamentals

Multiclass logistic/softmax regression from scratch

Sophia Yang Intermediate 5y ago

Introduction | Mathematics and statistics for data science and machine learning

ML Fundamentals

Introduction | Mathematics and statistics for data science and machine learning

codebasics Beginner 5y ago

What is logarithm? | Math, Statistics for data science, machine learning

ML Fundamentals ⚡ AI Lesson

What is logarithm? | Math, Statistics for data science, machine learning

codebasics Beginner 5y ago

Building Models with PyTorch

ML Fundamentals

Building Models with PyTorch

PyTorch Beginner 5y ago

Conversational AI w/ Jarvis - checking out the API

ML Fundamentals

Conversational AI w/ Jarvis - checking out the API

sentdex Beginner 5y ago

Autoviz-Automatically Visualize Any Dataset With Single Line Of Code

ML Fundamentals

Autoviz-Automatically Visualize Any Dataset With Single Line Of Code

Krish Naik Intermediate 4y ago

Who Are Data Scientists?

ML Fundamentals

Who Are Data Scientists?

Krish Naik Intermediate 4y ago

Deep Learning Interview Series #2- Asked In interview

ML Fundamentals

Deep Learning Interview Series #2- Asked In interview

Krish Naik Beginner 5y ago

L18.2: The GAN Objective

ML Fundamentals

L18.2: The GAN Objective

Sebastian Raschka Beginner 5y ago

L18.1: The Main Idea Behind GANs

ML Fundamentals

L18.1: The Main Idea Behind GANs

Sebastian Raschka Beginner 5y ago

L18.0: Introduction to Generative Adversarial Networks -- Lecture Overview

ML Fundamentals

L18.0: Introduction to Generative Adversarial Networks -- Lecture Overview

Sebastian Raschka Beginner 5y ago

Automating Web Scrapping Using AutoScraper Library

ML Fundamentals

Automating Web Scrapping Using AutoScraper Library

Krish Naik Intermediate 5y ago

L17.7 VAE Latent Space Arithmetic in PyTorch -- Making People Smile (Code Example)

ML Fundamentals

L17.7 VAE Latent Space Arithmetic in PyTorch -- Making People Smile (Code Example)

Sebastian Raschka Beginner 5y ago

L17.6 A Variational Autoencoder for Face Images in PyTorch -- Code Example

ML Fundamentals

L17.6 A Variational Autoencoder for Face Images in PyTorch -- Code Example

Sebastian Raschka Beginner 5y ago

L17.5 A Variational Autoencoder for Handwritten Digits in PyTorch -- Code Example

ML Fundamentals

L17.5 A Variational Autoencoder for Handwritten Digits in PyTorch -- Code Example

Sebastian Raschka Beginner 5y ago

L17.4 Variational Autoencoder Loss Function

ML Fundamentals

L17.4 Variational Autoencoder Loss Function

Sebastian Raschka Beginner 5y ago

L17.3 The Log-Var Trick

ML Fundamentals

L17.3 The Log-Var Trick

Sebastian Raschka Beginner 5y ago

L17.2 Sampling from a Variational Autoencoder

ML Fundamentals

L17.2 Sampling from a Variational Autoencoder

Sebastian Raschka Beginner 5y ago

L17.1 Variational Autoencoder Overview

ML Fundamentals

L17.1 Variational Autoencoder Overview

Sebastian Raschka Beginner 5y ago

L17.0 Intro to Variational Autoencoders -- Lecture Overview

ML Fundamentals

L17.0 Intro to Variational Autoencoders -- Lecture Overview

Sebastian Raschka Beginner 5y ago

Machine Learning Interview Series#1-Asked in Interview

ML Fundamentals

Machine Learning Interview Series#1-Asked in Interview

Krish Naik Beginner 5y ago

War Stories Productionising ML // Nick Masca // Coffee Session#35

ML Fundamentals

War Stories Productionising ML // Nick Masca // Coffee Session#35

MLOps.community Beginner 5y ago

Introduction To Machine Learning And Deep Learning For Starters

ML Fundamentals

Introduction To Machine Learning And Deep Learning For Starters

Krish Naik Beginner 5y ago

Deep Learning Interview Series #1- Asked In Interview

ML Fundamentals

Deep Learning Interview Series #1- Asked In Interview

Krish Naik Beginner 5y ago

Friday Live Q&A Ask Anything Related Data Science

ML Fundamentals

Friday Live Q&A Ask Anything Related Data Science

Krish Naik Beginner 5y ago

L16.5 Other Types of Autoencoders

ML Fundamentals

L16.5 Other Types of Autoencoders

Sebastian Raschka Beginner 5y ago

L16.4 A Convolutional Autoencoder in PyTorch -- Code Example

ML Fundamentals

L16.4 A Convolutional Autoencoder in PyTorch -- Code Example

Sebastian Raschka Beginner 5y ago

L16.3 Convolutional Autoencoders & Transposed Convolutions

ML Fundamentals

L16.3 Convolutional Autoencoders & Transposed Convolutions

Sebastian Raschka Beginner 5y ago

L16.2 A Fully-Connected Autoencoder

ML Fundamentals

L16.2 A Fully-Connected Autoencoder

Sebastian Raschka Beginner 5y ago

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Production Machine Learning Systems

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Production Machine Learning Systems

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Generative AI: Foundations and Concepts

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Generative AI: Foundations and Concepts

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Computer Vision Fundamentals with Google Cloud

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Computer Vision Fundamentals with Google Cloud

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Doğrusal Cebir II: Kare Matrisler, Hesaplama Yöntemleri ve Uygulamalar / Linear Algebra II: Square Matrices, Calculation Methods and Applications

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Doğrusal Cebir II: Kare Matrisler, Hesaplama Yöntemleri ve Uygulamalar / Linear Algebra II: Square Matrices, Calculation Methods and Applications

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Calculus for Machine Learning and Data Science

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Calculus for Machine Learning and Data Science

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Física: Vectores, Trabajo y Energía

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Física: Vectores, Trabajo y Energía

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Medical Insurance Premium Prediction with Machine Learning

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Medical Insurance Premium Prediction with Machine Learning

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Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation - Bahasa Indonesia

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Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation - Bahasa Indonesia

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Information Extraction from Free Text Data in Health

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Information Extraction from Free Text Data in Health

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Smart Analytics, Machine Learning, and AI on GCP em Português Brasileiro

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Smart Analytics, Machine Learning, and AI on GCP em Português Brasileiro

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AI for Medical Prognosis

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Machine Learning - Anomaly Detection via PyCaret

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Machine Learning - Anomaly Detection via PyCaret

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AI & Machine Learning: Apply, Build & Solve

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AI & Machine Learning: Apply, Build & Solve

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Machine Learning Foundations

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Machine Learning Foundations

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Python Essentials for MLOps

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Python Essentials for MLOps

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Introduction to Data Management

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Introduction to Data Management

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Algorithm Alchemy: Unlocking the Secrets of Machine Learning

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Algorithm Alchemy: Unlocking the Secrets of Machine Learning

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Reading and Writing Files

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Reading and Writing Files

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