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📐 ML Fundamentals

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

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Build Your Own PyTorch Trainer!
ML Fundamentals
Build Your Own PyTorch Trainer!
Abhishek Thakur Beginner 5y ago
Handling Imbalanced Dataset Using Cost Sensitive Neural Networks- Credit Card Fraud Detection
ML Fundamentals
Handling Imbalanced Dataset Using Cost Sensitive Neural Networks- Credit Card Fraud Detection
Krish Naik Intermediate 5y ago
10.8 K-fold CV 1-Standard Error Method -- Code Example (L10: Model Evaluation 3)
ML Fundamentals
10.8 K-fold CV 1-Standard Error Method -- Code Example (L10: Model Evaluation 3)
Sebastian Raschka Beginner 5y ago
10.7 K-fold CV 1-Standard Error Method (L10: Model Evaluation 3)
ML Fundamentals ⚡ AI Lesson
10.7 K-fold CV 1-Standard Error Method (L10: Model Evaluation 3)
Sebastian Raschka Beginner 5y ago
Peter Norvig – Singularity Is in the Eye of the Beholder
ML Fundamentals
Peter Norvig – Singularity Is in the Eye of the Beholder
Weights & Biases Beginner 5y ago
Supervised vs Unsupervised vs Reinforcement Learning | Machine Learning Tutorial | Simplilearn
6:27
ML Fundamentals ⚡ AI Lesson
Supervised vs Unsupervised vs Reinforcement Learning | Machine Learning Tutorial | Simplilearn
Simplilearn Beginner 5y ago
Ineuron's Affordable BI And ML DL Course With Remote Internship From 21st November
ML Fundamentals
Ineuron's Affordable BI And ML DL Course With Remote Internship From 21st November
Krish Naik Beginner 5y ago
Convert python file to exe in less than 2 minutes (.py to .exe)
ML Fundamentals
Convert python file to exe in less than 2 minutes (.py to .exe)
codebasics Beginner 5y ago
🏺 Version Control Data and Models with W&B Artifacts
ML Fundamentals
🏺 Version Control Data and Models with W&B Artifacts
Weights & Biases Intermediate 5y ago
Break into AI: I took an online course, what's next?
ML Fundamentals ⚡ AI Lesson
Break into AI: I took an online course, what's next?
DeepLearningAI Beginner 5y ago
AdaBoost : Data Science Concepts
ML Fundamentals ⚡ AI Lesson
AdaBoost : Data Science Concepts
ritvikmath Intermediate 5y ago
Data Science and Employee Productivity with Nicki | 365 Data Use Cases
ML Fundamentals
Data Science and Employee Productivity with Nicki | 365 Data Use Cases
365 Data Science Beginner 5y ago
How to Perform Large-Scale Image Classification | Grandmaster Series E2
ML Fundamentals
How to Perform Large-Scale Image Classification | Grandmaster Series E2
NVIDIA Developer Advanced 5y ago
Impute missing values using KNNImputer or IterativeImputer
ML Fundamentals
Impute missing values using KNNImputer or IterativeImputer
Data School Beginner 5y ago
Loss Functions : Data Science Basics
ML Fundamentals
Loss Functions : Data Science Basics
ritvikmath Beginner 5y ago
Build a Voice Assistant using Javascript w/Tensorflow | For Beginners
ML Fundamentals
Build a Voice Assistant using Javascript w/Tensorflow | For Beginners
CoderOne Beginner 5y ago
Getting ready to learn Python, Windows edition #5: Writing and running Python program
ML Fundamentals
Getting ready to learn Python, Windows edition #5: Writing and running Python program
Brandon Rohrer Beginner 5y ago
Getting ready to learn Python, Windows edition #4: Installing and running Python
ML Fundamentals
Getting ready to learn Python, Windows edition #4: Installing and running Python
Brandon Rohrer Beginner 5y ago
Talks # 14: Martin Henze; Knowledge is Power: Understanding your Data through EDA and Visualisations
ML Fundamentals ⚡ AI Lesson
Talks # 14: Martin Henze; Knowledge is Power: Understanding your Data through EDA and Visualisations
Abhishek Thakur Beginner 5y ago
Osmo Wonderland - Perfect Christmas Gift For Kids
ML Fundamentals
Osmo Wonderland - Perfect Christmas Gift For Kids
NPStation Beginner 5y ago
Pytorch Conditional GAN Tutorial
ML Fundamentals
Pytorch Conditional GAN Tutorial
Aladdin Persson Beginner 5y ago
Set a "random_state" to make your code reproducible
ML Fundamentals
Set a "random_state" to make your code reproducible
Data School Beginner 5y ago
Ep#2 - What are regulations saying about data privacy?
ML Fundamentals
Ep#2 - What are regulations saying about data privacy?
MLOps.community Beginner 5y ago
How Deep Learning has Revolutionized OCR with Cha Zhang - #416
ML Fundamentals ⚡ AI Lesson
How Deep Learning has Revolutionized OCR with Cha Zhang - #416
The TWIML AI Podcast with Sam Charrington Beginner 5y ago
Let's Build a Language Translator! LIVE
ML Fundamentals ⚡ AI Lesson
Let's Build a Language Translator! LIVE
Siraj Raval Intermediate 5y ago
10.6 K-fold CV for Model Evaluation -- Code Examples (L10: Model Evaluation 3)
ML Fundamentals
10.6 K-fold CV for Model Evaluation -- Code Examples (L10: Model Evaluation 3)
Sebastian Raschka Beginner 5y ago
10.5 K-fold CV for Model Selection (L10: Model Evaluation 3)
ML Fundamentals ⚡ AI Lesson
10.5 K-fold CV for Model Selection (L10: Model Evaluation 3)
Sebastian Raschka Beginner 5y ago
10.4 K-fold CV for Model Evaluation -- Code Examples (L10: Model Evaluation 3)
ML Fundamentals ⚡ AI Lesson
10.4 K-fold CV for Model Evaluation -- Code Examples (L10: Model Evaluation 3)
Sebastian Raschka Beginner 5y ago
10.3 K-fold CV for Model Evaluation (L10: Model Evaluation 3)
ML Fundamentals
10.3 K-fold CV for Model Evaluation (L10: Model Evaluation 3)
Sebastian Raschka Beginner 5y ago
10.2 Hyperparameters (L10: Model Evaluation 3)
ML Fundamentals
10.2 Hyperparameters (L10: Model Evaluation 3)
Sebastian Raschka Beginner 5y ago
10.1 Cross-validation Lecture Overview (L10: Model Evaluation 3)
ML Fundamentals
10.1 Cross-validation Lecture Overview (L10: Model Evaluation 3)
Sebastian Raschka Beginner 5y ago
Debug your YOLOv5 experiments with Weights & Biases
ML Fundamentals ⚡ AI Lesson
Debug your YOLOv5 experiments with Weights & Biases
Weights & Biases Advanced 5y ago
Ineuron's Detailed Course Content Discussion Of ML And DL- Affordable AI Education
ML Fundamentals
Ineuron's Detailed Course Content Discussion Of ML And DL- Affordable AI Education
Krish Naik Intermediate 5y ago
Getting ready to learn Python, Windows edition #3: Creating and editing text files
ML Fundamentals
Getting ready to learn Python, Windows edition #3: Creating and editing text files
Brandon Rohrer Beginner 5y ago
Getting ready to learn Python, Windows edition #2: The command prompt
ML Fundamentals ⚡ AI Lesson
Getting ready to learn Python, Windows edition #2: The command prompt
Brandon Rohrer Beginner 5y ago
9.7 The .632 and .632+ Bootstrap methods (L09 Model Eval 2: Confidence Intervals)
ML Fundamentals
9.7 The .632 and .632+ Bootstrap methods (L09 Model Eval 2: Confidence Intervals)
Sebastian Raschka Beginner 5y ago
9.6 Bootstrap Confidence Intervals (L09 Model Eval 2: Confidence Intervals)
ML Fundamentals
9.6 Bootstrap Confidence Intervals (L09 Model Eval 2: Confidence Intervals)
Sebastian Raschka Beginner 5y ago
9.5 Resampling and Repeated Holdout (L09 Model Eval 2: Confidence Intervals)
ML Fundamentals ⚡ AI Lesson
9.5 Resampling and Repeated Holdout (L09 Model Eval 2: Confidence Intervals)
Sebastian Raschka Beginner 5y ago
Robert Nishihara — The State of Distributed Computing in ML
ML Fundamentals
Robert Nishihara — The State of Distributed Computing in ML
Weights & Biases Intermediate 5y ago
9.4 ML Confidence Intervals via Normal Approximation (L09 Model Eval 2: Confidence Intervals)
ML Fundamentals ⚡ AI Lesson
9.4 ML Confidence Intervals via Normal Approximation (L09 Model Eval 2: Confidence Intervals)
Sebastian Raschka Beginner 5y ago
9.3 Holdout Model Selection (L09 Model Eval 2: Confidence Intervals)
ML Fundamentals
9.3 Holdout Model Selection (L09 Model Eval 2: Confidence Intervals)
Sebastian Raschka Beginner 5y ago
Getting ready to learn Python, Windows edition #1: Files and directories
ML Fundamentals
Getting ready to learn Python, Windows edition #1: Files and directories
Brandon Rohrer Beginner 5y ago
9.2 Holdout Evaluation (L09 Model Eval 2: Confidence Intervals)
ML Fundamentals
9.2 Holdout Evaluation (L09 Model Eval 2: Confidence Intervals)
Sebastian Raschka Beginner 5y ago
9.1 Introduction (L09 Model Eval 2: Confidence Intervals)
ML Fundamentals
9.1 Introduction (L09 Model Eval 2: Confidence Intervals)
Sebastian Raschka Beginner 5y ago
TFIDF : Data Science Concepts
ML Fundamentals
TFIDF : Data Science Concepts
ritvikmath Intermediate 5y ago
Charles Frye on using machine learning to multiply by one
ML Fundamentals ⚡ AI Lesson
Charles Frye on using machine learning to multiply by one
Weights & Biases Intermediate 5y ago
Chirag Agarwal on detecting out-of-distribution data with Variance-of-Gradient
ML Fundamentals
Chirag Agarwal on detecting out-of-distribution data with Variance-of-Gradient
Weights & Biases Advanced 5y ago
⚡ Supercharge your Training with PyTorch Lightning + Weights & Biases
ML Fundamentals
⚡ Supercharge your Training with PyTorch Lightning + Weights & Biases
Weights & Biases Intermediate 5y ago
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Diabetes Prediction With Pyspark MLLIB
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Diabetes Prediction With Pyspark MLLIB
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IA Para Todos (Português)
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IA Para Todos (Português)
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Recommender Systems
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Recommender Systems
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Precalculus: Periodic Functions
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Precalculus: Periodic Functions
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Deep Learning with PyTorch : Siamese Network
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Deep Learning with PyTorch : Siamese Network
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Optimize Deep Learning Models for Peak AI
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Optimize Deep Learning Models for Peak AI
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