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📐 ML Fundamentals

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

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Deep learning project end to end | Potato Disease Classification - 3 : Model Building
ML Fundamentals ⚡ AI Lesson
Deep learning project end to end | Potato Disease Classification - 3 : Model Building
codebasics Beginner 4y ago
Introduction to Statistics | 365 Data Science Courses
ML Fundamentals
Introduction to Statistics | 365 Data Science Courses
365 Data Science Beginner 4y ago
Kaggle's 30 Days Of ML (Competition Part-4): Hyperparameter tuning using Optuna
ML Fundamentals ⚡ AI Lesson
Kaggle's 30 Days Of ML (Competition Part-4): Hyperparameter tuning using Optuna
Abhishek Thakur Beginner 4y ago
What is Interpretable Machine Learning - ML Explainability - with Python LIME Shap Tutorial
ML Fundamentals
What is Interpretable Machine Learning - ML Explainability - with Python LIME Shap Tutorial
1littlecoder Beginner 4y ago
Affordable Machine Learning And Advance Deep Learning Course From iNeuron
ML Fundamentals
Affordable Machine Learning And Advance Deep Learning Course From iNeuron
Krish Naik Beginner 4y ago
Robot Dogs: A Programmer's Best Friend
ML Fundamentals
Robot Dogs: A Programmer's Best Friend
sentdex Beginner 4y ago
Kaggle 30 Days of ML (Day 18) - SHAP - Shapley Values - Interpretable Machine Learning - XAI
ML Fundamentals
Kaggle 30 Days of ML (Day 18) - SHAP - Shapley Values - Interpretable Machine Learning - XAI
1littlecoder Beginner 4y ago
Deep learning project end to end | Potato Disease Classification Using CNN - 1 : Problem Statement
ML Fundamentals ⚡ AI Lesson
Deep learning project end to end | Potato Disease Classification Using CNN - 1 : Problem Statement
codebasics Beginner 4y ago
How to Monitor Machine Learning Models (Evidently AI)
ML Fundamentals ⚡ AI Lesson
How to Monitor Machine Learning Models (Evidently AI)
Data Professor Beginner 4y ago
Tesla AI Day Highlights | Lex Fridman
ML Fundamentals ⚡ AI Lesson
Tesla AI Day Highlights | Lex Fridman
Lex Fridman Beginner 4y ago
Coding Linear Trees! : Data Science Code
ML Fundamentals
Coding Linear Trees! : Data Science Code
ritvikmath Beginner 4y ago
Is Data Visualization Important for Data Science? (A Data Scientist's Perspective)
ML Fundamentals ⚡ AI Lesson
Is Data Visualization Important for Data Science? (A Data Scientist's Perspective)
Ken Jee Beginner 4y ago
Why do we care about cross-correlations vs convolutions | ❓ #AICoffeeBreakQuiz #Shorts
ML Fundamentals
Why do we care about cross-correlations vs convolutions | ❓ #AICoffeeBreakQuiz #Shorts
AI Coffee Break with Letitia Beginner 4y ago
Kaggle's 30 Days Of ML (Competition Part-3): What is Target Encoding and how does it work?
ML Fundamentals ⚡ AI Lesson
Kaggle's 30 Days Of ML (Competition Part-3): What is Target Encoding and how does it work?
Abhishek Thakur Beginner 4y ago
W&B Fastbook Reading Group — 11. Introduction to convolutions
ML Fundamentals ⚡ AI Lesson
W&B Fastbook Reading Group — 11. Introduction to convolutions
Weights & Biases Beginner 4y ago
Josh Bloom — The Link Between Astronomy and ML
ML Fundamentals
Josh Bloom — The Link Between Astronomy and ML
Weights & Biases Beginner 4y ago
Convolution vs Cross-Correlation. How most CNNs do not compute convolutions. | ❓ #Shorts
ML Fundamentals
Convolution vs Cross-Correlation. How most CNNs do not compute convolutions. | ❓ #Shorts
AI Coffee Break with Letitia Beginner 4y ago
Four ways to examine the steps of a Pipeline
ML Fundamentals ⚡ AI Lesson
Four ways to examine the steps of a Pipeline
Data School Beginner 4y ago
Computer Scientist Explains Machine Learning in 5 Levels of Difficulty | WIRED
ML Fundamentals
Computer Scientist Explains Machine Learning in 5 Levels of Difficulty | WIRED
WIRED Beginner 4y ago
If You Are Losing Motivation While Learning Data Science- Hear This Story Out️‍🔥️‍🔥️‍🔥️‍🔥️‍🔥
ML Fundamentals
If You Are Losing Motivation While Learning Data Science- Hear This Story Out️‍🔥️‍🔥️‍🔥️‍🔥️‍🔥
Krish Naik Beginner 4y ago
Python for Data Science | Beginner Friendly Full Course in 5 Hours
ML Fundamentals
Python for Data Science | Beginner Friendly Full Course in 5 Hours
Nicholas Renotte Beginner 4y ago
Save a model or Pipeline using joblib
ML Fundamentals
Save a model or Pipeline using joblib
Data School Beginner 4y ago
Creating MLOps Standards // Alex Chung and Srivathsan Canchi // MLOps Coffee Sessions #50
ML Fundamentals
Creating MLOps Standards // Alex Chung and Srivathsan Canchi // MLOps Coffee Sessions #50
MLOps.community Beginner 4y ago
SRGAN implementation from scratch
ML Fundamentals ⚡ AI Lesson
SRGAN implementation from scratch
Aladdin Persson Beginner 4y ago
Kaggle 30 Days of ML (Day 17) - Partial Dependence Plot - Interpretable Machine Learning - XAI
ML Fundamentals
Kaggle 30 Days of ML (Day 17) - Partial Dependence Plot - Interpretable Machine Learning - XAI
1littlecoder Beginner 4y ago
Kaggle 30 Days of ML (Day 16) - Feature Importance of Machine Learning with ELI5
ML Fundamentals
Kaggle 30 Days of ML (Day 16) - Feature Importance of Machine Learning with ELI5
1littlecoder Beginner 4y ago
Kaggle's 30 Days Of ML (Competition Part-2): Feature Engineering (Categorical & Numerical Variables)
ML Fundamentals ⚡ AI Lesson
Kaggle's 30 Days Of ML (Competition Part-2): Feature Engineering (Categorical & Numerical Variables)
Abhishek Thakur Beginner 4y ago
Object detection on an RC car with W&B and YOLOv5
ML Fundamentals
Object detection on an RC car with W&B and YOLOv5
Weights & Biases Beginner 4y ago
Kaggle 30 Days of ML (Day 15) - Interpretable Machine Learning Use-cases
ML Fundamentals
Kaggle 30 Days of ML (Day 15) - Interpretable Machine Learning Use-cases
1littlecoder Beginner 4y ago
FastAPI Tutorial | FastAPI vs Flask
ML Fundamentals ⚡ AI Lesson
FastAPI Tutorial | FastAPI vs Flask
codebasics Beginner 4y ago
How to avoid Google Colab Session Runtime from Closing with JavaScript?
ML Fundamentals
How to avoid Google Colab Session Runtime from Closing with JavaScript?
1littlecoder Beginner 4y ago
Kaggle's 30 Days Of ML (Competition Part-1): Cross Validation & First Submission on Kaggle
ML Fundamentals
Kaggle's 30 Days Of ML (Competition Part-1): Cross Validation & First Submission on Kaggle
Abhishek Thakur Beginner 4y ago
Kaggle 30 Days of ML (Day 14) - XGBoost, Data Leakage - Learn Python ML in 30 Days
ML Fundamentals
Kaggle 30 Days of ML (Day 14) - XGBoost, Data Leakage - Learn Python ML in 30 Days
1littlecoder Beginner 4y ago
Kaggle 30 Days of ML (Day 13) - Scikit-Learn Pipeline, CrossValidation - Learn Python ML in 30 Days
ML Fundamentals
Kaggle 30 Days of ML (Day 13) - Scikit-Learn Pipeline, CrossValidation - Learn Python ML in 30 Days
1littlecoder Beginner 4y ago
Kaggle's 30 Days Of ML (Day-14 Part-2): What is Data Leakage?
ML Fundamentals
Kaggle's 30 Days Of ML (Day-14 Part-2): What is Data Leakage?
Abhishek Thakur Beginner 4y ago
Kaggle's 30 Days Of ML (Day-14 Part-1): Intro to XGBoost
ML Fundamentals ⚡ AI Lesson
Kaggle's 30 Days Of ML (Day-14 Part-1): Intro to XGBoost
Abhishek Thakur Beginner 4y ago
Kaggle 30 Days of ML - Day 12 - Kaggle Missing Values, Encoding - Learn Python ML in 30 Days
ML Fundamentals
Kaggle 30 Days of ML - Day 12 - Kaggle Missing Values, Encoding - Learn Python ML in 30 Days
1littlecoder Beginner 4y ago
Kaggle's 30 Days Of ML (Day-13 Part-2): Cross-validation
ML Fundamentals ⚡ AI Lesson
Kaggle's 30 Days Of ML (Day-13 Part-2): Cross-validation
Abhishek Thakur Beginner 4y ago
Kaggle's 30 Days Of ML (Day-13 Part-1): Scikit-Learn Pipelines
ML Fundamentals
Kaggle's 30 Days Of ML (Day-13 Part-1): Scikit-Learn Pipelines
Abhishek Thakur Beginner 4y ago
Is age a barrier to learn data science?
ML Fundamentals
Is age a barrier to learn data science?
codebasics Beginner 4y ago
Quantization in deep learning | Deep Learning Tutorial 49 (Tensorflow, Keras & Python)
ML Fundamentals ⚡ AI Lesson
Quantization in deep learning | Deep Learning Tutorial 49 (Tensorflow, Keras & Python)
codebasics Beginner 4y ago
Kaggle's 30 Days Of ML (Day-12 Part-1): Handling Missing Values in Datasets (imputing missing value)
ML Fundamentals ⚡ AI Lesson
Kaggle's 30 Days Of ML (Day-12 Part-1): Handling Missing Values in Datasets (imputing missing value)
Abhishek Thakur Beginner 4y ago
Kaggle 30 Days of ML - Day 11 - Kaggle Competition Submission - Learn Python ML in 30 Days
ML Fundamentals
Kaggle 30 Days of ML - Day 11 - Kaggle Competition Submission - Learn Python ML in 30 Days
1littlecoder Beginner 4y ago
W&B Fastbook Reading Group — 10. Movie recommendation using fastai
ML Fundamentals ⚡ AI Lesson
W&B Fastbook Reading Group — 10. Movie recommendation using fastai
Weights & Biases Beginner 4y ago
Kaggle's 30 Days Of ML (Day-11): Machine Learning Model to Predict House Prices (Intro to ML Ends)
ML Fundamentals ⚡ AI Lesson
Kaggle's 30 Days Of ML (Day-11): Machine Learning Model to Predict House Prices (Intro to ML Ends)
Abhishek Thakur Beginner 4y ago
Run VSCode In Web-Github Codespaces Introduction
ML Fundamentals
Run VSCode In Web-Github Codespaces Introduction
Krish Naik Beginner 4y ago
Kaggle 30 Days of ML - Day 10 - Overfitting, Random Forest - Learn Python ML in 30 Days
ML Fundamentals
Kaggle 30 Days of ML - Day 10 - Overfitting, Random Forest - Learn Python ML in 30 Days
1littlecoder Beginner 4y ago
Kaggle's 30 Days Of ML (Day-10): Underfitting, Overfitting & Random Forests
ML Fundamentals ⚡ AI Lesson
Kaggle's 30 Days Of ML (Day-10): Underfitting, Overfitting & Random Forests
Abhishek Thakur Beginner 4y ago
📚 Coursera Courses Opens on Coursera · Free to audit
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Breast Cancer Prediction Using Machine Learning
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Self-paced
Breast Cancer Prediction Using Machine Learning
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Apply Test-Driven ML Code
📚 Coursera Course ↗
Self-paced
Apply Test-Driven ML Code
Opens on Coursera ↗
Regression Analysis for Statistics & Machine Learning in R
📚 Coursera Course ↗
Self-paced
Regression Analysis for Statistics & Machine Learning in R
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Data Analytics and Machine Learning for Big Data
📚 Coursera Course ↗
Self-paced
Data Analytics and Machine Learning for Big Data
Opens on Coursera ↗
Applied Fundamentals: Guess the Number
📚 Coursera Course ↗
Self-paced
Applied Fundamentals: Guess the Number
Opens on Coursera ↗
Automate ML Pipelines for Peak Performance
📚 Coursera Course ↗
Self-paced
Automate ML Pipelines for Peak Performance
Opens on Coursera ↗