📐 ML Fundamentals

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

ML Fundamentals

Coding ARMA Model : Time Series Talk

ritvikmath Intermediate 5y ago

ML Fundamentals

Webinar: Admissions for University of North Texas Bachelor of Applied Arts and Sciences (B.A.A.S.)

Coursera Intermediate 5y ago

ML Fundamentals

Who Is The Best Person To Judge You? Motivational Talks

Krish Naik Intermediate 5y ago

ML Fundamentals

Live Q&A Data Science

Krish Naik Intermediate 5y ago

ML Fundamentals ⚡ AI Lesson

Linear Regression Normal Equation Python

Aladdin Persson Intermediate 5y ago

ML Fundamentals ⚡ AI Lesson

Jack Clark — Building Trustworthy AI Systems

Weights & Biases Intermediate 6y ago

ML Fundamentals ⚡ AI Lesson

MA Model Code Example : Time Series Talk

ritvikmath Intermediate 6y ago

ML Fundamentals ⚡ AI Lesson

Shortcut Learning in Deep Neural Networks

Yannic Kilcher Intermediate 6y ago

ML Fundamentals

Who has the highest standards in ML?

MLOps.community Intermediate 6y ago

ML Fundamentals

Survivorship Bias in machine learning tutorials

MLOps.community Intermediate 6y ago

ML Fundamentals

Tips N Tricks #6: How to train multiple deep neural networks on TPUs simultaneously

Abhishek Thakur Intermediate 6y ago

ML Fundamentals ⚡ AI Lesson

Inside TensorFlow: TF Debugging

TensorFlow Intermediate 6y ago

ML Fundamentals ⚡ AI Lesson

Theory: Applications of Data Science

DataCamp Intermediate 6y ago

ML Fundamentals ⚡ AI Lesson

Computer Vision is Not Perfect

Data Skeptic Intermediate 6y ago

ML Fundamentals

10K Subscribers: Approaching (almost) Any Machine Learning Problem and Talk Show

Abhishek Thakur Intermediate 6y ago

ML Fundamentals

How to build custom Datasets for Images in Pytorch

Aladdin Persson Intermediate 6y ago

ML Fundamentals ⚡ AI Lesson

Taming Kerberos - Computerphile

Computerphile Intermediate 6y ago

ML Fundamentals ⚡ AI Lesson

Oxford Impact Measurement Programme - The Landscape of Impact Measurement for Impact Investing

Saïd Business School, University of Oxford Intermediate 6y ago

ML Fundamentals

Nicolas Koumchatzky — Machine Learning in Production for Self-Driving Cars

Weights & Biases Intermediate 6y ago

ML Fundamentals

Humans in the Loop are a defining factor in Machine Learning

MLOps.community Intermediate 6y ago

ML Fundamentals

Sharing My Experience- How Teaching Has Improved My Data Science Skills

Krish Naik Intermediate 6y ago

ML Fundamentals

Specific challenges in Machine Learning

MLOps.community Intermediate 6y ago

ML Fundamentals

MLOps: Airflow Pros and Cons

MLOps.community Intermediate 6y ago

ML Fundamentals

MLOps meetup #5 High Stakes ML: Active Failures, Latent Factors with Flavio Clesio

MLOps.community Intermediate 6y ago

ML Fundamentals

How to Build A Data Science Portfolio That Can Get You Jobs?

Krish Naik Intermediate 6y ago

ML Fundamentals

Live Q&A Data Science

Krish Naik Intermediate 6y ago

ML Fundamentals

How Should You Explain Your Data Science Projects To Recruiters?- Must Watch For Everyone

Krish Naik Intermediate 6y ago

ML Fundamentals

3 key parts to Machine Learning monitoring

MLOps.community Intermediate 6y ago

ML Fundamentals

Auto retrain ML models is not the question

MLOps.community Intermediate 6y ago

ML Fundamentals

Developing a Machine Learning Feature Store

MLOps.community Intermediate 6y ago

ML Fundamentals

Evolution of the ML feature store @SurveyMonkey

MLOps.community Intermediate 6y ago

ML Fundamentals

Doing ML with Personal Information

MLOps.community Intermediate 6y ago

ML Fundamentals

How do you handle ML version control at SurveyMonkey

MLOps.community Intermediate 6y ago

ML Fundamentals

Hybrid Data Science Teams @SurveyMonkey

MLOps.community Intermediate 6y ago

ML Fundamentals

Message buses, Async and sync architecture

MLOps.community Intermediate 6y ago

ML Fundamentals

ML Services Gateway at SurveyMonkey

MLOps.community Intermediate 6y ago

ML Fundamentals

ML Platforms - The build vs buy question

MLOps.community Intermediate 6y ago

ML Fundamentals ⚡ AI Lesson

How to save and load models in Pytorch

Aladdin Persson Intermediate 6y ago

ML Fundamentals

My Recording Gears For Data Science Videos

Krish Naik Intermediate 6y ago

ML Fundamentals

Pytorch GoogLeNet / InceptionNet implementation from scratch

Aladdin Persson Intermediate 6y ago

ML Fundamentals

Why Domain Knowledge Is Important For Data Scientist?

Krish Naik Intermediate 6y ago

ML Fundamentals ⚡ AI Lesson

Pytorch CNN example (Convolutional Neural Network)

Aladdin Persson Intermediate 6y ago

ML Fundamentals

Pytorch Neural Network example

Aladdin Persson Intermediate 6y ago

ML Fundamentals

End to End Chatbot with Deployment And Custom Service Integration

Krish Naik Intermediate 6y ago

ML Fundamentals

Spearman's rank correlation coefficient- Statistics

Krish Naik Intermediate 6y ago

ML Fundamentals

Time Management- How Do I Efficiently Manage My Time? My Experience- Motivation

Krish Naik Intermediate 6y ago

ML Fundamentals

Saturday Live Q&A

Krish Naik Intermediate 6y ago

ML Fundamentals

MLOps Manifesto with Luke Marsden from Dotscience

MLOps.community Intermediate 6y ago

📚 Coursera Courses Opens on Coursera · Free to audit

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Self-paced

Using BigQuery Machine Learning for inference

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Foundations of Machine Learning

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Introduction to Thermodynamics: Transferring Energy from Here to There

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Self-paced

Foundations of Data Science and Machine Learning with Python

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Self-paced

Çok değişkenli Fonksiyon II: Uygulamalar / Multivariable Calculus II: Applications

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Self-paced

Fundamentals of CNNs and RNNs

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Interest Rate Models

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Optimize Deep Learning Models for Peak AI

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I/O-efficient algorithms

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Production Machine Learning Systems - Português Brasileiro

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Model Training & Evaluation

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Introduction to Applied Machine Learning

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Introduction to Machine Learning

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Data for Machine Learning

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Breast Cancer Prediction Using Machine Learning

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Self-paced

NumPy, Matplotlib & Pandas – Data Science Prerequisites

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Introduction to Machine Learning: Unsupervised Learning

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Cloud Machine Learning Engineering and MLOps

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