📐 ML Fundamentals

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

ML Fundamentals

Operationalizing Machine Learning at a Large Financial Institution // Daniel Stahl //MLOps Meetup#56

MLOps.community Beginner 5y ago

ML Fundamentals

Day 4- MLOPS Continuous Integration And Model Tracking Using MLFlow- Machine Learning

Krish Naik Beginner 5y ago

ML Fundamentals

MARCH MADNESS - Will My Machine Learning Model Beat Your Bracket?

Ken Jee Beginner 5y ago

ML Fundamentals

L13.4 Convolutional Filters and Weight-Sharing

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L13.3 Convolutional Neural Network Basics

Sebastian Raschka Beginner 5y ago

ML Fundamentals

Day 3- MLOPS End To End Implementation With Deployment- Machine Learning

Krish Naik Beginner 5y ago

ML Fundamentals

ProGAN Paper Walkthrough

Aladdin Persson Beginner 5y ago

ML Fundamentals ⚡ AI Lesson

CycleGAN implementation from scratch

Aladdin Persson Beginner 5y ago

ML Fundamentals

Learn TensorFlow and Deep Learning fundamentals with Python (code-first introduction) Part 1/2

Daniel Bourke Beginner 5y ago

ML Fundamentals

Me he CAPTURADO en 3D... ¡DENTRO de una Red Neuronal! (y tú también puedes 👀)

Dot CSV Beginner 5y ago

ML Fundamentals ⚡ AI Lesson

How you SHOULD code Machine Learning

CodeEmporium Beginner 5y ago

ML Fundamentals

Artificial intelligence Or Machine Learning #Shorts

Manish Sharma Beginner 5y ago

ML Fundamentals

Will AI replace network engineers?

David Bombal Beginner 5y ago

ML Fundamentals

Convolutional Autoencoder for Image Denoising - Keras Code Examples

Connor Shorten Beginner 5y ago

ML Fundamentals

Converting words to numbers, Word Embeddings | Deep Learning Tutorial 39 (Tensorflow & Python)

codebasics Beginner 5y ago

ML Fundamentals ⚡ AI Lesson

How to Avoid Suffering in MLOps/Data Engineering Role // Igor Lushchyk // MLOps Meetup #55

MLOps.community Beginner 5y ago

ML Fundamentals ⚡ AI Lesson

Dave Selinger — AI and the Next Generation of Security Systems

Weights & Biases Beginner 5y ago

ML Fundamentals

AI and Gaming Research Summit 2021 - Understanding Players (Day 2 Track 1.2)

Microsoft Research Beginner 5y ago

ML Fundamentals ⚡ AI Lesson

Expectations with Machine Learning

CodeEmporium Beginner 5y ago

ML Fundamentals

PyTorch Time Sequence Prediction With LSTM - Forecasting Tutorial

Patrick Loeber Beginner 5y ago

ML Fundamentals

L13.0 Introduction to Convolutional Networks -- Lecture Overview

Sebastian Raschka Beginner 5y ago

ML Fundamentals

Day 2- MLOPS End To End Implementation From Basics- Machine Learning

Krish Naik Beginner 5y ago

ML Fundamentals

L12.6 Additional Topics and Research on Optimization Algorithms

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L12.5 Choosing Different Optimizers in PyTorch

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L12.4 Adam: Combining Adaptive Learning Rates and Momentum

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L12.3 SGD with Momentum

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L12.2 Learning Rate Schedulers in PyTorch

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L12.1 Learning Rate Decay

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L12.0: Improving Gradient Descent-based Optimization -- Lecture Overview

Sebastian Raschka Beginner 5y ago

ML Fundamentals

Day 1- MLOPS End To End Implementation- Machine Learning

Krish Naik Beginner 5y ago

ML Fundamentals ⚡ AI Lesson

TensorFlow DCGAN Tutorial

Aladdin Persson Beginner 5y ago

ML Fundamentals

MLOps Live Community Session Announcement

Krish Naik Beginner 5y ago

ML Fundamentals

L11.7 Weight Initialization in PyTorch -- Code Example

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L11.6 Xavier Glorot and Kaiming He Initialization

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L11.5 Weight Initialization -- Why Do We Care?

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L11.4 Why BatchNorm Works

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L11.3 BatchNorm in PyTorch -- Code Example

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L11.2 How BatchNorm Works

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L11.1 Input Normalization

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L11.0 Input Normalization and Weight Initialization -- Lecture Overview

Sebastian Raschka Beginner 5y ago

ML Fundamentals

Waste Classification Machine Learning Classification Project-Waste Recycling

Krish Naik Beginner 5y ago

ML Fundamentals

CycleGAN Paper Walkthrough

Aladdin Persson Beginner 5y ago

ML Fundamentals

L10.5.4 Dropout in PyTorch

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L10.4 L2 Regularization for Neural Nets

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L10.2 Data Augmentation in PyTorch

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L10.0 Regularization Methods for Neural Networks -- Lecture Overview

Sebastian Raschka Beginner 5y ago

ML Fundamentals ⚡ AI Lesson

Pix2Pix implementation from scratch

Aladdin Persson Beginner 5y ago

ML Fundamentals ⚡ AI Lesson

How (and why) you should undervolt your GPU - A step by step guide (Deep Learning/Gaming/Mining)

Aladdin Persson Beginner 5y ago

📚 Coursera Courses Opens on Coursera · Free to audit

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Introduction to AI and Machine Learning on GC - Español

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Modeling Data in the Tidyverse

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📚 Coursera Course ↗

Self-paced

Introduction to Generative AI - Bahasa Indonesia

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📚 Coursera Course ↗

Self-paced

Cómputo evolutivo

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📚 Coursera Course ↗

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Master Java Build Tools for ML Projects

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📚 Coursera Course ↗

Self-paced

Deep Learning with PyTorch : Image Segmentation

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📚 Coursera Course ↗

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Applied Machine Learning and Model Optimization

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Image Captioning with TensorFlow & Streamlit

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Analysis of Algorithms

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Çok değişkenli Fonksiyon I: Kavramlar / Multivariable Calculus I: Concepts

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Calculus through Data & Modeling: Limits & Derivatives

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Generative AI for Data Science

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Encoder-Decoder Architecture

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Databricks Machine Learning Quickstart

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Creative AI: Sound, Music and Interaction

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Responsible AI: Applying AI Principles with GC - Français

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Infraestrutura de IA: Cloud TPUs

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Applied Fundamentals: Guess the Number

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