📐 ML Fundamentals

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

ML Fundamentals

Getting ready to learn Python, Windows edition #2: The command prompt

Brandon Rohrer Beginner 5y ago

ML Fundamentals

9.7 The .632 and .632+ Bootstrap methods (L09 Model Eval 2: Confidence Intervals)

Sebastian Raschka Beginner 5y ago

ML Fundamentals

9.6 Bootstrap Confidence Intervals (L09 Model Eval 2: Confidence Intervals)

Sebastian Raschka Beginner 5y ago

ML Fundamentals

Talks # 14: Martin Henze; Knowledge is Power: Understanding your Data through EDA and Visualisations

Abhishek Thakur Beginner 5y ago

ML Fundamentals

Robert Nishihara — The State of Distributed Computing in ML

Weights & Biases Intermediate 5y ago

ML Fundamentals

Random Boolean Networks - Computerphile

Computerphile Intermediate 5y ago

ML Fundamentals

Getting ready to learn Python, Windows edition #1: Files and directories

Brandon Rohrer Beginner 5y ago

ML Fundamentals

The future of recruitment

Saïd Business School, University of Oxford Advanced 5y ago

ML Fundamentals

Pytorch Conditional GAN Tutorial

Aladdin Persson Beginner 5y ago

ML Fundamentals

Set a "random_state" to make your code reproducible

Data School Beginner 5y ago

ML Fundamentals

Ep#2 - What are regulations saying about data privacy?

MLOps.community Beginner 5y ago

ML Fundamentals

TFIDF : Data Science Concepts

ritvikmath Intermediate 5y ago

ML Fundamentals

How Deep Learning has Revolutionized OCR with Cha Zhang - #416

The TWIML AI Podcast with Sam Charrington Beginner 5y ago

ML Fundamentals

Charles Frye on using machine learning to multiply by one

Weights & Biases Intermediate 5y ago

ML Fundamentals

Let's Build a Language Translator! LIVE

Siraj Raval Intermediate 5y ago

ML Fundamentals

Add a missing indicator to encode "missingness" as a feature

Data School Beginner 5y ago

ML Fundamentals

The ROC Curve : Data Science Concepts

ritvikmath Beginner 5y ago

ML Fundamentals

Flow Physics Quantification in an Aneurysm Using NVIDIA PhysicsNeMo

NVIDIA Developer Beginner 5y ago

ML Fundamentals

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

Krish Naik Intermediate 5y ago

ML Fundamentals

Saturday Live Q&A Ask Anything Related Data Science

Krish Naik Intermediate 5y ago

ML Fundamentals

Chia liang Kao - Practical Enterprise JupyterHub Deployment and MLOps with PrimeHub| JupyterCon 2020

JupyterCon Intermediate 5y ago

ML Fundamentals

Karla Spuldaro - Building AI Pipelines with Elyra | JupyterCon 2020

JupyterCon Intermediate 5y ago

ML Fundamentals

AIDEN physio assistant by Shivay Lamba - Made with TensorFlow.js

TensorFlow Intermediate 5y ago

ML Fundamentals

When Machine Learning meets privacy - Episode 1

MLOps.community Beginner 5y ago

ML Fundamentals

This Book will Help you Land a Data Science Job

Data Professor Beginner 5y ago

ML Fundamentals

How to Build Classification Models (Weka Tutorial #2)

Data Professor Beginner 5y ago

ML Fundamentals

WGAN implementation from scratch (with gradient penalty)

Aladdin Persson Beginner 5y ago

ML Fundamentals

9.5 Resampling and Repeated Holdout (L09 Model Eval 2: Confidence Intervals)

Sebastian Raschka Beginner 5y ago

ML Fundamentals

9.4 ML Confidence Intervals via Normal Approximation (L09 Model Eval 2: Confidence Intervals)

Sebastian Raschka Beginner 5y ago

ML Fundamentals

9.3 Holdout Model Selection (L09 Model Eval 2: Confidence Intervals)

Sebastian Raschka Beginner 5y ago

ML Fundamentals

9.2 Holdout Evaluation (L09 Model Eval 2: Confidence Intervals)

Sebastian Raschka Beginner 5y ago

ML Fundamentals

9.1 Introduction (L09 Model Eval 2: Confidence Intervals)

Sebastian Raschka Beginner 5y ago

ML Fundamentals

Chirag Agarwal on detecting out-of-distribution data with Variance-of-Gradient

Weights & Biases Advanced 5y ago

ML Fundamentals

⚡ Supercharge your Training with PyTorch Lightning + Weights & Biases

Weights & Biases Intermediate 5y ago

ML Fundamentals

Important Interview Questions On Convolution Neural Network- Deep Learning

Krish Naik Intermediate 5y ago

ML Fundamentals

Joe Spisak-Deep Learning Development with PyTorch+Jupyter using Heterogenous hardware|JupyterCon2020

JupyterCon Beginner 5y ago

ML Fundamentals

Praveen Kanamarlapud - Kernel Life Cycle Management | JupyterCon 2020

JupyterCon Intermediate 5y ago

ML Fundamentals

Important Steps I Have Followed To Improve My Data Science Skills- Sharing My Experience

Krish Naik Beginner 5y ago

ML Fundamentals

8.5 Bias-Variance Decomposition of the 0/1 Loss (L08: Model Evaluation Part 1)

Sebastian Raschka Beginner 5y ago

ML Fundamentals

Use Pipeline to chain together multiple steps

Data School Beginner 5y ago

ML Fundamentals

Why There Are So Many Start Ups In AI, ML And DL? Important For Everyone

Krish Naik Beginner 5y ago

ML Fundamentals

8.4 Bias and Variance vs Overfitting and Underfitting (L08: Model Evaluation Part 1)

Sebastian Raschka Beginner 5y ago

ML Fundamentals

8.3 Bias-Variance Decomposition of the Squared Error (L08: Model Evaluation Part 1)

Sebastian Raschka Beginner 5y ago

ML Fundamentals

8.2 Intuition behind bias and variance (L08: Model Evaluation Part 1)

Sebastian Raschka Beginner 5y ago

ML Fundamentals

Curse of Dimensionality : Data Science Basics

ritvikmath Beginner 5y ago

ML Fundamentals

8.1 Intro to overfitting and underfitting (L08: Model Evaluation Part 1)

Sebastian Raschka Beginner 5y ago

ML Fundamentals

Devin Robison - Optimizing model performance | JupyterCon 2020

JupyterCon Intermediate 5y ago

ML Fundamentals

Deep Learning-All Optimizers In One Video-SGD with Momentum,Adagrad,Adadelta,RMSprop,Adam Optimizers

Krish Naik Intermediate 5y ago