📐 ML Fundamentals

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

ML Fundamentals

W&B Fastbook Reading Group — 5. SGD (Stochastic Gradient Descent)

Weights & Biases Beginner 4y ago

ML Fundamentals

Roger & DJ — The Rise of Big Data and CA's COVID-19 Response

Weights & Biases Beginner 4y ago

ML Fundamentals

Display GridSearchCV or RandomizedSearchCV results in a DataFrame

Data School Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

sin cos tan explained. Explanation using real life example | Math, Statistics for data science

codebasics Beginner 4y ago

ML Fundamentals

Thompson Sampling : Data Science Concepts

ritvikmath Beginner 4y ago

ML Fundamentals

How Deepfakes Work

Creator Academy Australia Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

Content-based filtering & collaborative filtering (Building recommendation systems with TensorFlow)

TensorFlow Intermediate 4y ago

ML Fundamentals ⚡ AI Lesson

Try RandomizedSearchCV if GridSearchCV is taking too long

Data School Beginner 4y ago

ML Fundamentals

Minimum Laptop Configuration To Start With Machine Learning And Deep Learning💻💻💻💻💻💻

Krish Naik Beginner 4y ago

ML Fundamentals

Generate Python Faster with Mito⭐ ⭐ ⭐ ⭐

Krish Naik Beginner 4y ago

ML Fundamentals

Writing a Python Script to Check If Any ACs Are Available Every 5 Minutes

CS Dojo Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

problems that solve themselves #shorts

ritvikmath Intermediate 4y ago

ML Fundamentals

How to build machine learning models for drug discovery using PaDELPy

Data Professor Beginner 4y ago

ML Fundamentals

Chow Yun Fat DeepFake

Creator Academy Australia Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

BERT Model for Toxic Comment Classification (with GitHub Copilot's help)

Abhishek Thakur Beginner 4y ago

ML Fundamentals

Self-driving from VISION ONLY - Tesla's self-driving progress by Andrej Karpathy (Talk Analysis)

Yannic Kilcher Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

Deep Unsupervised Learning for Climate Informatics with Claire Monteleoni - #497

The TWIML AI Podcast with Sam Charrington Beginner 4y ago

ML Fundamentals

All Python Libraries You Need For Machine Learning And Data Science

Patrick Loeber Beginner 4y ago

ML Fundamentals

PyTorch Community Voices | Distributed PyTorch with Ray | Michael & Richard

PyTorch Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

AI Weekly Update - June 30th, 2021 (#37!)

Connor Shorten Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

The Molecular Basis of Life

arXiv Insights Beginner 4y ago

ML Fundamentals

Introducing Retiarii: A deep learning exploratory-training framework on NNI

Microsoft Research Advanced 4y ago

ML Fundamentals ⚡ AI Lesson

Engineering MLOps // Emmanuel Raj // MLOps Meetup #69

MLOps.community Beginner 4y ago

ML Fundamentals

Maximizing Performance for Distributed Deep Learning with NVIDIA SHARP (HGX)

NVIDIA Developer Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

Build a ML Classification Model in 12 Lines with PyCaret

Nicholas Renotte Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

What is the Jax Deep Learning Framework?

Roboflow Beginner 4y ago

ML Fundamentals

Panels # 1: What it takes to become a Quadruple Kaggle Grandmaster?

Abhishek Thakur Beginner 4y ago

ML Fundamentals

Build A Machine Learning iOS App | PyTorch Mobile Deployment

Patrick Loeber Beginner 4y ago

ML Fundamentals

L3.4 Feynman Calculus: Higher-Order Diagrams

MIT OpenCourseWare Beginner 4y ago

ML Fundamentals

L3.5 Feynman Calculus: Divergency

MIT OpenCourseWare Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

Building AI models for healthcare (ML Tech Talks)

TensorFlow Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

CI/CD for MLOPS Definition // Monmayuri Ray // MLOps Coffee Sessions #41 short clip

MLOps.community Advanced 4y ago

ML Fundamentals

W&B Fastbook Reading Group — 4. Going Deeper into Computer Vision

Weights & Biases Beginner 4y ago

ML Fundamentals

Teaching an RC car to drive itself

Weights & Biases Beginner 4y ago

ML Fundamentals

Writing Machine Learning Pipelines And Deep Learning Code Using Github Copilot ⭐⭐⭐⭐⭐⭐

Krish Naik Beginner 4y ago

ML Fundamentals

Amelia & Filip — How Pandora Deploys ML Models into Production

Weights & Biases Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

Use cross_val_score and GridSearchCV on a Pipeline

Data School Beginner 4y ago

ML Fundamentals

Coding Word2Vec : Natural Language Processing

ritvikmath Beginner 4y ago

ML Fundamentals

Three reasons not to use drop='first' with OneHotEncoder

Data School Beginner 4y ago

ML Fundamentals

W&B Fastbook Reading Group — 3. DL Models in Production & Ethical Considerations

Weights & Biases Beginner 4y ago

ML Fundamentals

L3.2 Feynman Calculus: Fermi's Golden Rule

MIT OpenCourseWare Beginner 4y ago

ML Fundamentals

L3.3 Feynman Calculus: Toy Theory

MIT OpenCourseWare Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

L3.1 Feynman Calculus: Introduction

MIT OpenCourseWare Beginner 4y ago

ML Fundamentals

Luis Ceze — Accelerating Machine Learning Systems

Weights & Biases Advanced 4y ago

ML Fundamentals

HistGradientBoostingClassifier natively supports missing values

Data School Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

TFLite delegates

TensorFlow Intermediate 4y ago

ML Fundamentals

W&B Fastbook Reading Group — 2. DL Models in Production & Validation Sets

Weights & Biases Beginner 4y ago

ML Fundamentals

Word2Vec : Natural Language Processing

ritvikmath Intermediate 4y ago

📚 Coursera Courses Opens on Coursera · Free to audit

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Self-paced

Advanced ML Algorithms & Unsupervised Learning

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Self-paced

Pneumonia Classification using PyTorch

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📚 Coursera Course ↗

Self-paced

Calculus through Data & Modelling: Integration Applications

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📚 Coursera Course ↗

Self-paced

Physics 102 - AC Circuits and Maxwell's Equations

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📚 Coursera Course ↗

Self-paced

Data Prep for Machine Learning in Python

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📚 Coursera Course ↗

Self-paced

Infraestrutura de IA: Cloud TPUs

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📚 Coursera Course ↗

Self-paced

Advanced CNNs, Transfer Learning, and Recurrent Networks

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📚 Coursera Course ↗

Self-paced

Machine Learning Rapid Prototyping with IBM Watson Studio

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📚 Coursera Course ↗

Self-paced

Data Science with Python: Analyze & Visualize

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Self-paced

Essential Causal Inference Techniques for Data Science

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📚 Coursera Course ↗

Self-paced

Differential Equations Part II Series Solutions

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📚 Coursera Course ↗

Self-paced

Credit Default Prediction with Python: Apply & Analyze

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📚 Coursera Course ↗

Self-paced

Introduction to High-Performance and Parallel Computing

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📚 Coursera Course ↗

Self-paced

Machine Learning: an overview

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📚 Coursera Course ↗

Self-paced

Optimize Deep Learning Models for Peak AI

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📚 Coursera Course ↗

Self-paced

Machine Learning With Big Data

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Self-paced

Optimize Deep Learning: Tune PyTorch Models

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Self-paced

Interpretable machine learning applications: Part 3

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