📐 ML Fundamentals

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

ML Fundamentals

Deep Learning With PyTorch - Full Course

Patrick Loeber Beginner 5y ago

ML Fundamentals

How k-nearest neighbors works

Brandon Rohrer Beginner 5y ago

ML Fundamentals

Quick Fast Python EDA with Pandas Profiling - Kaggle Dataset Hands-on

1littlecoder Beginner 5y ago

ML Fundamentals

L8.5 Logistic Regression in PyTorch -- Code Example

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L8.4 Logits and Cross Entropy

Sebastian Raschka Beginner 5y ago

ML Fundamentals

YOLOv3 from Scratch

Aladdin Persson Advanced 5y ago

ML Fundamentals

MLOps Engineering Labs Recap // Part 1 // MLOps Coffee Sessions #30

MLOps.community Beginner 5y ago

ML Fundamentals

Principal Component Analysis (PCA) | Introduction & Example (Python) Code

Shaw Talebi Beginner 5y ago

ML Fundamentals

Rendering Volumes and Implicit Shapes in PyTorch3D

PyTorch Beginner 5y ago

ML Fundamentals

SVM Dual : Data Science Concepts

ritvikmath Beginner 5y ago

ML Fundamentals

How would a Data Scientist analyze Customer Churn?

CodeEmporium Beginner 5y ago

ML Fundamentals

GOOGLE FIRES AI ETHICS TEAM 📰 DEEP NEWS 📰

Aladdin Persson Beginner 5y ago

ML Fundamentals

Simple Explanation of GRU (Gated Recurrent Units) | Deep Learning Tutorial 37 (Tensorflow & Python)

codebasics Beginner 5y ago

ML Fundamentals

Chacha Cipher - Computerphile

Computerphile Intermediate 5y ago

ML Fundamentals

'Git for Data' - Who, What, How and Why? // Luke Feeney & Gavin Mendel-Gleason // MLOps Meetup #52

MLOps.community Beginner 5y ago

ML Fundamentals

Stochastic Gradient Descent and Deploying Your Python Scripts on the Web | Real Python Podcast #48

Real Python Beginner 5y ago

ML Fundamentals

Daphne Koller — Digital Biology and the Next Epoch of Science

Weights & Biases Beginner 5y ago

ML Fundamentals

Jim Keller: The Future of Computing, AI, Life, and Consciousness | Lex Fridman Podcast #162

Lex Fridman Beginner 5y ago

ML Fundamentals

PerceptiLabs-The Best Machine Learning Visual Modeling Tool-Train Deep Learning Neural Network

Krish Naik Intermediate 5y ago

ML Fundamentals

2020 PyTorch Summer Hackathon Winners Recap

PyTorch Beginner 5y ago

ML Fundamentals

Code With Me : Gibbs Sampling

ritvikmath Advanced 5y ago

ML Fundamentals

Javier Ideami on Loss Landscape Visualizations - W&B Salon

Weights & Biases Intermediate 5y ago

ML Fundamentals

IBM Applied AI Professional Certificate: Gain AI Skills on Coursera

Coursera Beginner 5y ago

ML Fundamentals

Explainable AI explained! | #2 By-design interpretable models with Microsofts InterpretML

DeepFindr Beginner 5y ago

ML Fundamentals

How to get started with Graph ML? (Blog walkthrough)

Aleksa Gordić - The AI Epiphany Beginner 5y ago

ML Fundamentals

How capital markets can take sustainability to the next level

Saïd Business School, University of Oxford Intermediate 5y ago

ML Fundamentals

Session On Different Types Of Loss Function In Deep Learning

Krish Naik Intermediate 5y ago

ML Fundamentals

An AI software able to detect and count plastic waste in the ocean

What's AI by Louis-François Bouchard Beginner 5y ago

ML Fundamentals

Ubicomp (Ubiquitous Computing) - Computerphile

Computerphile Intermediate 5y ago

ML Fundamentals

L8.3 Logistic Regression Loss Derivative and Training

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L8.2 Logistic Regression Loss Function

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L8.1 Logistic Regression as a Single-Layer Neural Network

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L8.0 Logistic Regression -- Lecture Overview

Sebastian Raschka Beginner 5y ago

ML Fundamentals

Deep Learning News #4, Feb 20 2021

Sebastian Raschka Beginner 5y ago

ML Fundamentals

Is Machine Learning by Andrew Ng on Coursera worth it in 2021? [Course Review]

Aladdin Persson Beginner 5y ago

ML Fundamentals

EfficientNet from scratch in Pytorch

Aladdin Persson Beginner 5y ago

ML Fundamentals

EfficientNet Paper Walkthrough

Aladdin Persson Beginner 5y ago

ML Fundamentals

L7.0 GPU resources & Google Colab

Sebastian Raschka Beginner 5y ago

ML Fundamentals

Javier Ideami on Loss Landscapes and the Flatland Perspective

Weights & Biases Beginner 5y ago

ML Fundamentals

L6.5 A Closer Look at the PyTorch API

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L6.4 Training ADALINE with PyTorch -- Code Example

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L6.3 Automatic Differentiation in PyTorch -- Code Example

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L6.2 Understanding Automatic Differentiation via Computation Graphs

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L6.1 Learning More About PyTorch

Sebastian Raschka Beginner 5y ago

ML Fundamentals

L6.0 Automatic Differentiation in PyTorch -- Lecture Overview

Sebastian Raschka Beginner 5y ago

ML Fundamentals

Coding MCMC : Data Science Code

ritvikmath Intermediate 5y ago

ML Fundamentals

How to solve Santander Kaggle Transaction Competition [Top 1% Solution, No Ensemble]

Aladdin Persson Beginner 5y ago

ML Fundamentals

Sunday Late Night Live Q&A - Ask Anything Related To Data Science

Krish Naik Intermediate 5y ago

📚 Coursera Courses Opens on Coursera · Free to audit

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Neural Networks and Deep Learning

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Analytic Combinatorics

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Reinforcement Learning

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📚 Coursera Course ↗

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Sequence Modeling, Transformers, and Transfer Learning

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Advanced Machine Learning with R: Apply & Predict

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Automate, Optimize, and Monitor ML Models

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Applied Unsupervised Learning in Python

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📚 Coursera Course ↗

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Machine Learning with PyTorch and Scikit-Learn

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📚 Coursera Course ↗

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Build & Optimize TensorFlow ML Workflows

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Google Cloud Speech API: Qwik Start

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📚 Coursera Course ↗

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Debug ML Code: Fix, Trace & Evaluate

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📚 Coursera Course ↗

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Optimize Deep Learning: Tune PyTorch Models

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📚 Coursera Course ↗

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Data Prep for Machine Learning in Python

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Apply Generative Adversarial Networks (GANs)

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📚 Coursera Course ↗

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Supervised Machine Learning: Regression

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MLOps Tools: MLflow and Hugging Face

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GenAI for Employee Engagement: Driving Real-Time Insights

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AI Essentials

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