📐 ML Fundamentals

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

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CLIP: El Ojo MÁS POTENTE de la INTELIGENCIA ARTIFICIAL!

ML Fundamentals

CLIP: El Ojo MÁS POTENTE de la INTELIGENCIA ARTIFICIAL!

Dot CSV Beginner 5y ago

Model & Data Drift Deep Dive // Ben Wilson // MLOps Meetup Clips

ML Fundamentals

Model & Data Drift Deep Dive // Ben Wilson // MLOps Meetup Clips

MLOps.community Intermediate 5y ago

TensorfFlow 2 Beginner Course (3 HOURS)

ML Fundamentals

TensorfFlow 2 Beginner Course (3 HOURS)

Patrick Loeber Beginner 5y ago

DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning

ML Fundamentals

DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning

Yannic Kilcher Beginner 5y ago

What Is Probation Period?General Q&A

ML Fundamentals

What Is Probation Period?General Q&A

Krish Naik Beginner 5y ago

The Art Of Writing Resume For Data Science- Must For EveryOne

ML Fundamentals

The Art Of Writing Resume For Data Science- Must For EveryOne

Krish Naik Beginner 5y ago

Tensorflow Object Detection in 5 Hours with Python | Full Course with 3 Projects

ML Fundamentals

Tensorflow Object Detection in 5 Hours with Python | Full Course with 3 Projects

Nicholas Renotte Intermediate 5y ago

L15.5 Long Short-Term Memory

ML Fundamentals

L15.5 Long Short-Term Memory

Sebastian Raschka Beginner 5y ago

L15.4 Backpropagation Through Time Overview

ML Fundamentals

L15.4 Backpropagation Through Time Overview

Sebastian Raschka Beginner 5y ago

Chris Mattmann — ML Applications on Earth, Mars, and Beyond

ML Fundamentals

Chris Mattmann — ML Applications on Earth, Mars, and Beyond

Weights & Biases Beginner 5y ago

Oxford AMLP - hybrid programme design Q&A session

ML Fundamentals ⚡ AI Lesson

Oxford AMLP - hybrid programme design Q&A session

Saïd Business School, University of Oxford Beginner 5y ago

PHD in machine learning or data science, is it worth?

ML Fundamentals

PHD in machine learning or data science, is it worth?

codebasics Beginner 5y ago

When to add more complexity in your ML infrastructure? // Daniel Stahl // MLOps Meetup Clips

ML Fundamentals

When to add more complexity in your ML infrastructure? // Daniel Stahl // MLOps Meetup Clips

MLOps.community Beginner 5y ago

How Neural Networks Can Be Hacked (And What You Should Do To Protect It)!

ML Fundamentals

How Neural Networks Can Be Hacked (And What You Should Do To Protect It)!

Patrick Loeber Beginner 5y ago

Scikit-learn Crash Course - Machine Learning Library for Python

ML Fundamentals

Scikit-learn Crash Course - Machine Learning Library for Python

freeCodeCamp.org Beginner 5y ago

PAIR AI Explorables | Is the problem in the data? Examples on Fairness, Diversity, and Bias.

ML Fundamentals

PAIR AI Explorables | Is the problem in the data? Examples on Fairness, Diversity, and Bias.

Yannic Kilcher Beginner 5y ago

ml5.js: Creative coding with ML for all - Made with TensorFlow.js

ML Fundamentals ⚡ AI Lesson

ml5.js: Creative coding with ML for all - Made with TensorFlow.js

TensorFlow Beginner 5y ago

Kmeans-based Blink Detecter DEMO

ML Fundamentals

Kmeans-based Blink Detecter DEMO

Shaw Talebi Beginner 5y ago

6. Dataloader in PyTorch

ML Fundamentals

6. Dataloader in PyTorch

Abhishek Thakur Beginner 5y ago

5. Dataset class for simple image / vision problems

ML Fundamentals

5. Dataset class for simple image / vision problems

Abhishek Thakur Beginner 5y ago

What is Word2Vec? A Simple Explanation | Deep Learning Tutorial 41 (Tensorflow, Keras & Python)

ML Fundamentals

What is Word2Vec? A Simple Explanation | Deep Learning Tutorial 41 (Tensorflow, Keras & Python)

codebasics Beginner 5y ago

Amazing Initiative For Kids- Ineuron K-12 Youtube Channel- Free Content #shorts

ML Fundamentals

Amazing Initiative For Kids- Ineuron K-12 Youtube Channel- Free Content #shorts

Krish Naik Intermediate 5y ago

How To Handle 90 Days Notice Period With HR

ML Fundamentals

How To Handle 90 Days Notice Period With HR

Krish Naik Intermediate 5y ago

Stats Interview Series #2-Asked In Interview

ML Fundamentals

Stats Interview Series #2-Asked In Interview

Krish Naik Intermediate 5y ago

L15.3 Different Types of Sequence Modeling Tasks

ML Fundamentals

L15.3 Different Types of Sequence Modeling Tasks

Sebastian Raschka Beginner 5y ago

L15.2 Sequence Modeling with RNNs

ML Fundamentals

L15.2 Sequence Modeling with RNNs

Sebastian Raschka Beginner 5y ago

L15.1: Different Methods for Working With Text Data

ML Fundamentals

L15.1: Different Methods for Working With Text Data

Sebastian Raschka Beginner 5y ago

L15.0: Introduction to Recurrent Neural Networks -- Lecture Overview

ML Fundamentals

L15.0: Introduction to Recurrent Neural Networks -- Lecture Overview

Sebastian Raschka Beginner 5y ago

Statistics-Left Skewed And Right Skewed Distribution And Relation With Mean, Median And Mode

ML Fundamentals

Statistics-Left Skewed And Right Skewed Distribution And Relation With Mean, Median And Mode

Krish Naik Beginner 5y ago

Stats Interview Series #1- Asked In Interview

ML Fundamentals

Stats Interview Series #1- Asked In Interview

Krish Naik Beginner 5y ago

Start-ups vs Enterprise OSS Strategy in Machine Learning Tooling // MLOps Clips with Sarah Catanzaro

ML Fundamentals ⚡ AI Lesson

Start-ups vs Enterprise OSS Strategy in Machine Learning Tooling // MLOps Clips with Sarah Catanzaro

MLOps.community Intermediate 5y ago

Interview Question -Risks In Data Science Projects

ML Fundamentals

Interview Question -Risks In Data Science Projects

Krish Naik Intermediate 5y ago

L14.6.2 Transfer Learning in PyTorch -- Code Example

ML Fundamentals

L14.6.2 Transfer Learning in PyTorch -- Code Example

Sebastian Raschka Beginner 5y ago

L14.6.1 Transfer Learning

ML Fundamentals

L14.6.1 Transfer Learning

Sebastian Raschka Beginner 5y ago

L14.5 Convolutional Instead of Fully Connected Layers

ML Fundamentals

L14.5 Convolutional Instead of Fully Connected Layers

Sebastian Raschka Beginner 5y ago

L14.4.2 All-Convolutional Network in PyTorch -- Code Example

ML Fundamentals

L14.4.2 All-Convolutional Network in PyTorch -- Code Example

Sebastian Raschka Beginner 5y ago

L14.4.1 Replacing Max-Pooling with Convolutional Layers

ML Fundamentals

L14.4.1 Replacing Max-Pooling with Convolutional Layers

Sebastian Raschka Beginner 5y ago

Shapash- Python Library To Make Machine Learning Interpretable

ML Fundamentals

Shapash- Python Library To Make Machine Learning Interpretable

Krish Naik Beginner 5y ago

MLOps Investments // Sarah Catanzaro // Coffee Session #33

ML Fundamentals ⚡ AI Lesson

MLOps Investments // Sarah Catanzaro // Coffee Session #33

MLOps.community Beginner 5y ago

Interesting Fact About Data #shorts

ML Fundamentals

Interesting Fact About Data #shorts

Krish Naik Beginner 5y ago

4. Dataset class for simple NLP problems

ML Fundamentals

4. Dataset class for simple NLP problems

Abhishek Thakur Beginner 5y ago

3. The dataset class in PyTorch

ML Fundamentals ⚡ AI Lesson

3. The dataset class in PyTorch

Abhishek Thakur Beginner 5y ago

2. PyTorch Autograd

ML Fundamentals

2. PyTorch Autograd

Abhishek Thakur Beginner 5y ago

1. Tensors in PyTorch

ML Fundamentals

1. Tensors in PyTorch

Abhishek Thakur Beginner 5y ago

Deployment Of ML Models Using PyWebIO And Flask

ML Fundamentals

Deployment Of ML Models Using PyWebIO And Flask

Krish Naik Beginner 5y ago

What Is P Value In Statistics In Simple Language?

ML Fundamentals

What Is P Value In Statistics In Simple Language?

Krish Naik Beginner 5y ago

Creating BMI Calculator Web APP Using Python And PyWebIO

ML Fundamentals

Creating BMI Calculator Web APP Using Python And PyWebIO

Krish Naik Beginner 5y ago

PyWebIO- Creating WebAPP Using Python Without Using HTML And JS

ML Fundamentals

PyWebIO- Creating WebAPP Using Python Without Using HTML And JS

Krish Naik Beginner 5y ago

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Data Science Challenge

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Data Science Challenge

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Optimize Deep Learning: Stabilize and Diagnose Models

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Optimize Deep Learning: Stabilize and Diagnose Models

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Master Java Build Tools for ML Projects

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Master Java Build Tools for ML Projects

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DevOps and AI on AWS: AIOps

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DevOps and AI on AWS: AIOps

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DP-100 Microsoft Azure DS Exam

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DP-100 Microsoft Azure DS Exam

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📚 Coursera Course ↗

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NumPy, Matplotlib & Pandas – Data Science Prerequisites

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NumPy, Matplotlib & Pandas – Data Science Prerequisites

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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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KALKÜLÜS II: TEMEL KAVRAMLAR / CALCULUS II: BASIC CONCEPTS

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KALKÜLÜS II: TEMEL KAVRAMLAR / CALCULUS II: BASIC CONCEPTS

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ML Pipelines on Google Cloud - Français

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Encoder-Decoder Architecture - Italiano

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Machine Learning in the Enterprise - Español

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Machine Learning in the Enterprise - Español

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MongoDB Aggregation Framework

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MongoDB Aggregation Framework

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Follow a Machine Learning Workflow

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Introduction to Self-Driving Cars

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Introduction to Self-Driving Cars

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Machine Learning with PySpark

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Machine Learning with PySpark

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Managing Machine Learning Models

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Managing Machine Learning Models

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Advanced Neural Network Techniques

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Advanced Neural Network Techniques

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