🤖 Machine Learning Math

The mathematical backbone of machine learning—linear algebra, probability, optimization, and statistics—presented for those who want to understand the engines beneath the algorithms.

Machine Learning for Dummies

by John Paul Mueller • 2016

Machine learning demystified: pick the right algorithm, train it well, and know when it works.

3.53

139

🧠 Machine Learning Basics 📊 Data Science Basics 🏷️ Supervised Learning 📈 Statistical Learning 🔮 Predictive Modeling

Machine Learning for Dummies 93%

Machine learning demystified: pick the right algorithm, train it well, and know when it works.

by John Paul Mueller 2016

3.53

139 ratings

🧠 Machine Learning Basics 📊 Data Science Basics 🏷️ Supervised Learning 📈 Statistical Learning 🔮 Predictive Modeling

The Hundred-Page Machine Learning Book

by Andriy Burkov • 2019

The one-sitting machine learning education: a hundred pages, no code, every algorithm that matters.

4.25

1k+

🤖 Machine Learning 📊 Data Science 📚 Classical Machine Learning 📈 Statistical Learning 🏫 Supervised Learning

The Hundred-Page Machine Learning Book Summary

The Hundred-Page Machine Learning Book 93%

The one-sitting machine learning education: a hundred pages, no code, every algorithm that matters.

by Andriy Burkov 2019

4.25

1k+ ratings

🤖 Machine Learning 📊 Data Science 📚 Classical Machine Learning 📈 Statistical Learning 🏫 Supervised Learning

Introduction To Machine Learning

by Ethem Alpaydin • 2004

The mathematical core of machine learning, taught without cutting corners: from Bayes to boosting.

3.78

251

🤖 Machine Learning 📊 Statistical Learning 🏷️ Supervised Learning 🎮 Reinforcement Learning 🎲 Bayesian Inference

Introduction To Machine Learning Summary

Introduction To Machine Learning 93%

The mathematical core of machine learning, taught without cutting corners: from Bayes to boosting.

by Ethem Alpaydin 2004

3.78

251 ratings

🤖 Machine Learning 📊 Statistical Learning 🏷️ Supervised Learning 🎮 Reinforcement Learning 🎲 Bayesian Inference

Why Machines Learn

by Anil Ananthaswamy • 2024

The perceptron flopped but the math stayed: the linear algebra and calculus that built the AI age.

4.38

1k+

📜 History Of Ai 🧬 Deep Learning 🧠 Neural Network Theory 📐 Linear Algebra 🔢 Mathematical Foundations

Why Machines Learn 93%

The perceptron flopped but the math stayed: the linear algebra and calculus that built the AI age.

by Anil Ananthaswamy 2024

4.38

1k+ ratings

📜 History Of Ai 🧬 Deep Learning 🧠 Neural Network Theory 📐 Linear Algebra 🔢 Mathematical Foundations

Neural Network for Beginners

by Sebastian Klaas • 2021

Stop treating neural networks as magic. Build them from scratch in Python, line by line.

5.00

🧠 Machine Learning 🧬 Deep Learning 🔗 Neural Networks 🔧 From Scratch Coding 👁️ Image Recognition

Neural Network for Beginners 93%

Stop treating neural networks as magic. Build them from scratch in Python, line by line.

by Sebastian Klaas 2021

5.00

1 ratings

🧠 Machine Learning 🧬 Deep Learning 🔗 Neural Networks 🔧 From Scratch Coding 👁️ Image Recognition

Machine Learning

by Dr Ruchi Doshi • 2021

From training models with labeled data to finding hidden patterns: the algorithms behind modern AI.

5.00

🧠 Machine Learning 📊 Supervised Learning 🧬 Deep Learning 🕹️ Reinforcement Learning 🛠️ Feature Engineering

Machine Learning 92%

From training models with labeled data to finding hidden patterns: the algorithms behind modern AI.

by Dr Ruchi Doshi 2021

5.00

1 ratings

🧠 Machine Learning 📊 Supervised Learning 🧬 Deep Learning 🕹️ Reinforcement Learning 🛠️ Feature Engineering

Deep Learning

by John D. Kelleher • 2019

Deep learning isn't clever math. It's simple neurons, wired at scale, learning from their mistakes.

3.89

473

🔬 Deep Learning 🧠 Neural Networks 🤖 Machine Learning 📘 Ai Fundamentals 🔗 Connectionism

Deep Learning 92%

Deep learning isn't clever math. It's simple neurons, wired at scale, learning from their mistakes.

by John D. Kelleher 2019

3.89

473 ratings

🔬 Deep Learning 🧠 Neural Networks 🤖 Machine Learning 📘 Ai Fundamentals 🔗 Connectionism

Hands-On Machine Learning with Scikit-Learn and TensorFlow

by Aurélien Géron • 2017

How neural networks remember: training RNNs, LSTMs, and GRUs for tasks where order matters.

4.55

3k+

🧠 Deep Learning 🔗 Neural Networks 🛠️ Practical Ml 📈 Time Series Forecasting 💬 Natural Language Processing

Hands-On Machine Learning with Scikit-Learn and TensorFlow Summary

Hands-On Machine Learning with Scikit-Learn and TensorFlow 92%

How neural networks remember: training RNNs, LSTMs, and GRUs for tasks where order matters.

by Aurélien Géron 2017

4.55

3k+ ratings

🧠 Deep Learning 🔗 Neural Networks 🛠️ Practical Ml 📈 Time Series Forecasting 💬 Natural Language Processing

Introduction to Linear Algebra

by Gilbert Strang • 1993

Linear algebra organized around a matrix's core spaces: from elimination straight to the SVD.

4.24

703

📐 Applied Linear Algebra 🧩 Matrix Factorizations ↔️ Vector Spaces 💻 Computational Mathematics ⚙️ Engineering Mathematics

Introduction to Linear Algebra 92%

Linear algebra organized around a matrix's core spaces: from elimination straight to the SVD.

by Gilbert Strang 1993

4.24

703 ratings

📐 Applied Linear Algebra 🧩 Matrix Factorizations ↔️ Vector Spaces 💻 Computational Mathematics ⚙️ Engineering Mathematics

Machine Learning For Absolute Beginners

by Oliver Theobald • 2018

A plain English path from zero to a working model: the algorithms, data prep, and code.

3.96

786

🤖 Machine Learning Basics 🐍 Python For Data Science 🧹 Data Preparation 🎯 Supervised Learning 🧠 Neural Networks

Machine Learning For Absolute Beginners Summary

Machine Learning For Absolute Beginners 92%

A plain English path from zero to a working model: the algorithms, data prep, and code.

by Oliver Theobald 2018

3.96

786 ratings

🤖 Machine Learning Basics 🐍 Python For Data Science 🧹 Data Preparation 🎯 Supervised Learning 🧠 Neural Networks

Numsense! Data Science for the Layman

by Annalyn Ng • 2017

Data science without the math: twelve techniques, what they do, and why intuition alone falls short.

4.14

622

🧠 Data Literacy 🤖 Machine Learning Basics 📈 Predictive Analytics 📊 Data-Driven Decisions 📘 Technical Primers

Numsense! Data Science for the Layman Summary

Numsense! Data Science for the Layman 92%

Data science without the math: twelve techniques, what they do, and why intuition alone falls short.

by Annalyn Ng 2017

4.14

622 ratings

🧠 Data Literacy 🤖 Machine Learning Basics 📈 Predictive Analytics 📊 Data-Driven Decisions 📘 Technical Primers

Machine Learning For Absolute Beginners

by Oliver Theobald • 2017

How machine learning algorithms think, from regression to neural networks, no math required.

4.12

474

🧠 Machine Learning 🧹 Data Preparation ⚖️ Model Evaluation 🏷️ Supervised Learning 🌳 Decision Trees

Machine Learning For Absolute Beginners 92%

How machine learning algorithms think, from regression to neural networks, no math required.

by Oliver Theobald 2017

4.12

474 ratings

🧠 Machine Learning 🧹 Data Preparation ⚖️ Model Evaluation 🏷️ Supervised Learning 🌳 Decision Trees

Python Machine Learning Case Studies

by Danish Haroon • 2017

Five Python case studies in machine learning: from data cleanup to a scored model, step by step.

2.60

📊 Data Science 🤖 Machine Learning 🔍 Exploratory Data Analysis ⚙️ Feature Engineering 📐 Model Evaluation

Python Machine Learning Case Studies Summary

Python Machine Learning Case Studies 92%

Five Python case studies in machine learning: from data cleanup to a scored model, step by step.

by Danish Haroon 2017

2.60

5 ratings

📊 Data Science 🤖 Machine Learning 🔍 Exploratory Data Analysis ⚙️ Feature Engineering 📐 Model Evaluation

Data Science from Scratch

by Joel Grus • 2015

Real understanding comes from building algorithms yourself, not calling libraries others wrote.

3.90

1k+

🐍 Python For Data Science ⚙️ Algorithm Implementation 📊 Statistical Thinking 📐 Applied Linear Algebra 🤖 Machine Learning Basics

Data Science from Scratch 92%

Real understanding comes from building algorithms yourself, not calling libraries others wrote.

by Joel Grus 2015

3.90

1k+ ratings

🐍 Python For Data Science ⚙️ Algorithm Implementation 📊 Statistical Thinking 📐 Applied Linear Algebra 🤖 Machine Learning Basics

Machine Learning Simplified

by Andrew Wolf • 2022

Supervised learning, gently: pipeline, optimization, and the real reasons your model overfits.

4.87

193

🎯 Supervised Learning 📚 Machine Learning Fundamentals 📊 Statistical Learning ✅ Model Evaluation 🧹 Data Preprocessing

Machine Learning Simplified 92%

Supervised learning, gently: pipeline, optimization, and the real reasons your model overfits.

by Andrew Wolf 2022

4.87

193 ratings

🎯 Supervised Learning 📚 Machine Learning Fundamentals 📊 Statistical Learning ✅ Model Evaluation 🧹 Data Preprocessing

Machine Learning

by Ethem Alpaydin • 2016

From spam filters to self-driving cars: the algorithms that learn from data, and what comes next.

3.62

1k+

🧠 Machine Learning 🕸️ Neural Networks 🔬 Deep Learning 🎮 Reinforcement Learning 📈 Statistical Learning

Machine Learning 92%

From spam filters to self-driving cars: the algorithms that learn from data, and what comes next.

by Ethem Alpaydin 2016

3.62

1k+ ratings

🧠 Machine Learning 🕸️ Neural Networks 🔬 Deep Learning 🎮 Reinforcement Learning 📈 Statistical Learning

AI and Machine Learning for Coders

by Laurence Moroney • 2021

Turn your code into AI that runs everywhere: train, optimize, deploy with a single toolkit.

4.09

108

🤖 Machine Learning 🧠 Deep Learning 🔵 Tensorflow 👁️ Computer Vision 💬 Nlp

AI and Machine Learning for Coders Summary

AI and Machine Learning for Coders 92%

Turn your code into AI that runs everywhere: train, optimize, deploy with a single toolkit.

by Laurence Moroney 2021

4.09

108 ratings

🤖 Machine Learning 🧠 Deep Learning 🔵 Tensorflow 👁️ Computer Vision 💬 Nlp

Python Data Science Handbook

by Jake VanderPlas • 2016

Four libraries, one workflow: the Python path from raw data to validated predictions.

4.29

676

📊 Data Science 🤖 Machine Learning 🐍 Scientific Python 🧹 Data Preprocessing ⚙️ Feature Engineering

Python Data Science Handbook 92%

Four libraries, one workflow: the Python path from raw data to validated predictions.

by Jake VanderPlas 2016

4.29

676 ratings

📊 Data Science 🤖 Machine Learning 🐍 Scientific Python 🧹 Data Preprocessing ⚙️ Feature Engineering

Python for Geeks

by Muhammad Asif • 2021

Machine learning from notebook to production: Python libraries, data prep, and deployment paths.

4.50

🐍 Python Programming ⚙️ Machine Learning Engineering 📊 Data Science 🚀 Production Deployment ☁️ Serverless Computing

Python for Geeks 92%

Machine learning from notebook to production: Python libraries, data prep, and deployment paths.

by Muhammad Asif 2021

4.50

8 ratings

🐍 Python Programming ⚙️ Machine Learning Engineering 📊 Data Science 🚀 Production Deployment ☁️ Serverless Computing

Algorithms of the Intelligent Web

by Haralambos Marmanis • 2009

Search, recommend, cluster, classify: the algorithms that make web applications intelligent.

3.62

130

🤖 Machine Learning 🌐 Web Applications 🎯 Recommendation Systems 📄 Text Mining ⛏️ Data Mining

Algorithms of the Intelligent Web Summary

Algorithms of the Intelligent Web 92%

Search, recommend, cluster, classify: the algorithms that make web applications intelligent.

by Haralambos Marmanis 2009

3.62

130 ratings

🤖 Machine Learning 🌐 Web Applications 🎯 Recommendation Systems 📄 Text Mining ⛏️ Data Mining

Neural Networks, Fuzzy Logic And Genetic Algorithms

by S. Rajasekaran • 2004

Soft computing's three pillars each have blind spots. This is how they fill each other's gaps.

4.21

151

🖥️ Soft Computing 🧠 Neural Networks 🌫️ Fuzzy Logic 🧬 Genetic Algorithms 🤖 Machine Learning

Neural Networks, Fuzzy Logic And Genetic Algorithms Summary

Neural Networks, Fuzzy Logic And Genetic Algorithms 92%

Soft computing's three pillars each have blind spots. This is how they fill each other's gaps.

by S. Rajasekaran 2004

4.21

151 ratings

🖥️ Soft Computing 🧠 Neural Networks 🌫️ Fuzzy Logic 🧬 Genetic Algorithms 🤖 Machine Learning

Keras Reinforcement Learning Projects

by Giuseppe Ciaburro • 2018

Nine Keras projects that bring reinforcement learning from theory to working self-learning agents.

4.00

🤖 Reinforcement Learning 🧠 Deep Learning 🔗 Neural Networks 🛠️ Project-Based Learning 🕹️ Game Playing Ai

Keras Reinforcement Learning Projects Summary

Keras Reinforcement Learning Projects 92%

Nine Keras projects that bring reinforcement learning from theory to working self-learning agents.

by Giuseppe Ciaburro 2018

4.00

1 ratings

🤖 Reinforcement Learning 🧠 Deep Learning 🔗 Neural Networks 🛠️ Project-Based Learning 🕹️ Game Playing Ai

Machine Learning with R

by Brett Lantz • 2015

Build the algorithms that catch spam, flag fraud, and recommend products: a hands-on guide in R.

4.20

312

💻 R Language 🤖 Machine Learning 📈 Predictive Modeling 🏷️ Supervised Learning 📊 Classification Algorithms

Machine Learning with R 92%

Build the algorithms that catch spam, flag fraud, and recommend products: a hands-on guide in R.

by Brett Lantz 2015

4.20

312 ratings

💻 R Language 🤖 Machine Learning 📈 Predictive Modeling 🏷️ Supervised Learning 📊 Classification Algorithms

Deep Learning with Python

by François Chollet • 2017

The Keras creator teaches you to build neural networks that see, read, and create in Python.

4.57

1k+

🧠 Deep Learning 🐍 Python Programming 🏋️ Model Training 👁️ Computer Vision 💬 Natural Language Processing

Deep Learning with Python 92%

The Keras creator teaches you to build neural networks that see, read, and create in Python.

by François Chollet 2017

4.57

1k+ ratings

🧠 Deep Learning 🐍 Python Programming 🏋️ Model Training 👁️ Computer Vision 💬 Natural Language Processing

Practical Time Series Analysis

by Aileen Nielsen • 2019

When ARIMA beats deep learning, and when it doesn't: the pipeline from cleaning to prediction.

3.77

📈 Time Series Analysis 🔧 Feature Engineering 🧹 Data Preparation ⚙️ Machine Learning Pipelines 📊 Statistical Learning

Practical Time Series Analysis 92%

When ARIMA beats deep learning, and when it doesn't: the pipeline from cleaning to prediction.

by Aileen Nielsen 2019

3.77

64 ratings

📈 Time Series Analysis 🔧 Feature Engineering 🧹 Data Preparation ⚙️ Machine Learning Pipelines 📊 Statistical Learning

The Master Algorithm

by Pedro Domingos • 2015

Machine learning's rival schools share a hidden core. Finding it could unlock general intelligence.

3.73

6k+

🤖 Machine Learning 📚 Popular Science 🧠 Superintelligence 📊 Big Data ⚖️ Ai Ethics

The Master Algorithm 92%

Machine learning's rival schools share a hidden core. Finding it could unlock general intelligence.

by Pedro Domingos 2015

3.73

6k+ ratings

🤖 Machine Learning 📚 Popular Science 🧠 Superintelligence 📊 Big Data ⚖️ Ai Ethics

AI for Data Science

by Zacharias Voulgaris • 2018

The real AI toolkit goes beyond deep learning: optimization, fuzzy logic, ensembles.

4.55

📊 Data Science 🧠 Deep Learning ⚙️ Optimization Algorithms 🤝 Ensemble Methods 📈 Big Data Analytics

AI for Data Science 92%

The real AI toolkit goes beyond deep learning: optimization, fuzzy logic, ensembles.

by Zacharias Voulgaris 2018

4.55

20 ratings

📊 Data Science 🧠 Deep Learning ⚙️ Optimization Algorithms 🤝 Ensemble Methods 📈 Big Data Analytics

Java Deep Learning Essentials

by Yusuke Sugomori • 2016

Python demos deep learning; Java deploys it. Architectures and libraries to close the gap.

3.20

🧠 Deep Learning ☕ Java Machine Learning 🔧 Practical Deep Learning 👁️ Computer Vision 🗣️ Natural Language Processing

Java Deep Learning Essentials 91%

Python demos deep learning; Java deploys it. Architectures and libraries to close the gap.

by Yusuke Sugomori 2016

3.20

5 ratings

🧠 Deep Learning ☕ Java Machine Learning 🔧 Practical Deep Learning 👁️ Computer Vision 🗣️ Natural Language Processing

Designing Machine Learning Systems

by Chip Huyen • 2022

Accuracy is not enough. An iterative playbook for machine learning systems that survive production.

4.45

1k+

⚙️ Machine Learning Engineering 🔧 Mlops 🔄 Iterative Design 📋 Reproducible Ml 🤝 Ensemble Learning

Designing Machine Learning Systems Summary

Designing Machine Learning Systems 91%

Accuracy is not enough. An iterative playbook for machine learning systems that survive production.

by Chip Huyen 2022

4.45

1k+ ratings

⚙️ Machine Learning Engineering 🔧 Mlops 🔄 Iterative Design 📋 Reproducible Ml 🤝 Ensemble Learning

Low-Code AI

by Gwendolyn Stripling • 2023

Skip Python. Train regression models, engineer features, and explain predictions, all in SQL.

4.33

🛠️ Practical Ml 📊 Data Exploration 🔧 Feature Engineering 🔍 Model Interpretability 🧩 Low-Code Platforms

Low-Code AI 91%

Skip Python. Train regression models, engineer features, and explain predictions, all in SQL.

by Gwendolyn Stripling 2023

4.33

6 ratings

🛠️ Practical Ml 📊 Data Exploration 🔧 Feature Engineering 🔍 Model Interpretability 🧩 Low-Code Platforms

The Little Book of Deep Learning

by François Fleuret • 2023

The machinery of deep learning, compressed: gradient descent, backprop, and attention.

4.32

151

🧠 Deep Learning 🔧 Model Architectures ⚡ Hardware Acceleration 📚 Supervised Learning 🎨 Generative Models

The Little Book of Deep Learning Summary

The Little Book of Deep Learning 91%

The machinery of deep learning, compressed: gradient descent, backprop, and attention.

by François Fleuret 2023

4.32

151 ratings

🧠 Deep Learning 🔧 Model Architectures ⚡ Hardware Acceleration 📚 Supervised Learning 🎨 Generative Models

Fundamentals of Machine Learning for Predictive Data Analytics

by John D. Kelleher • 2015

Pick the right machine learning approach for any business problem, guided by real case studies.

4.35

105

📊 Predictive Analytics 💼 Business Analytics 🤖 Supervised Learning 📈 Model Evaluation 🧹 Data Preparation

Fundamentals of Machine Learning for Predictive Data Analytics Summary

Fundamentals of Machine Learning for Predictive Data Analytics 91%

Pick the right machine learning approach for any business problem, guided by real case studies.

by John D. Kelleher 2015

4.35

105 ratings

📊 Predictive Analytics 💼 Business Analytics 🤖 Supervised Learning 📈 Model Evaluation 🧹 Data Preparation

Artificial Intelligence and Machine Learning for Business

by Steven Finlay • 2018

ML projects fail for business reasons, not technical ones. The rules for getting it right.

4.14

207

🤖 Machine Learning Basics 📊 Predictive Analytics 👔 AI For Managers 📈 Data-Driven Strategy ⚖️ Ethical AI

Artificial Intelligence and Machine Learning for Business Summary

Artificial Intelligence and Machine Learning for Business 91%

ML projects fail for business reasons, not technical ones. The rules for getting it right.

by Steven Finlay 2018

4.14

207 ratings

🤖 Machine Learning Basics 📊 Predictive Analytics 👔 AI For Managers 📈 Data-Driven Strategy ⚖️ Ethical AI

Introduction to Machine Learning with Python

by Andreas C. Müller • 2015

Build models that generalize, not just memorize: a Python data scientist's guide.

4.33

600

🤖 Applied Machine Learning 📊 Data Science 🏷️ Supervised Learning 🐍 Scikit-Learn 🔧 Feature Engineering

Introduction to Machine Learning with Python Summary

Introduction to Machine Learning with Python 91%

Build models that generalize, not just memorize: a Python data scientist's guide.

by Andreas C. Müller 2015

4.33

600 ratings

🤖 Applied Machine Learning 📊 Data Science 🏷️ Supervised Learning 🐍 Scikit-Learn 🔧 Feature Engineering

The Elements of Statistical Learning

by Trevor Hastie • 2001

The unified mathematical engine under linear regression, trees, and neural nets.

4.43

2k+

📊 Statistical Learning 🎯 Supervised Learning ✅ Model Evaluation 🤝 Ensemble Learning ⚖️ Regularization Methods

The Elements of Statistical Learning Summary

The Elements of Statistical Learning 91%

The unified mathematical engine under linear regression, trees, and neural nets.

by Trevor Hastie 2001

4.43

2k+ ratings

📊 Statistical Learning 🎯 Supervised Learning ✅ Model Evaluation 🤝 Ensemble Learning ⚖️ Regularization Methods

Algorithms

by Panos Louridas • 2020

Twenty steps to find one item in a million, and the hidden logic that runs our world.

4.03

302

📐 Algorithm Design 💻 Computing Primers 🕸️ Graph Theory 🔍 Search Algorithms 📊 Data Sorting

Algorithms 91%

Twenty steps to find one item in a million, and the hidden logic that runs our world.

by Panos Louridas 2020

4.03

302 ratings

📐 Algorithm Design 💻 Computing Primers 🕸️ Graph Theory 🔍 Search Algorithms 📊 Data Sorting

AIQ

by Nick Polson • 2018

What a 19th-century nurse and a lost submarine reveal about the algorithms that now run your life.

4.15

742

🤖 Ai Explainers 📊 History Of Statistics 🎲 Bayesian Thinking 🔮 Prediction And Forecasting 🤝 Human-Machine Collaboration

AIQ 91%

What a 19th-century nurse and a lost submarine reveal about the algorithms that now run your life.

by Nick Polson 2018

4.15

742 ratings

🤖 Ai Explainers 📊 History Of Statistics 🎲 Bayesian Thinking 🔮 Prediction And Forecasting 🤝 Human-Machine Collaboration

Introduction to Computation and Programming Using Python

by John V. Guttag • 2013

A computer calculates and remembers; everything beyond that is what you build with code.

4.22

500

🧑‍💻 Introductory Programming 🧠 Computational Thinking 🐍 Python For Beginners 📐 Algorithm Design 🗃️ Data Structures

Introduction to Computation and Programming Using Python Summary

Introduction to Computation and Programming Using Python 91%

A computer calculates and remembers; everything beyond that is what you build with code.

by John V. Guttag 2013

4.22

500 ratings

🧑‍💻 Introductory Programming 🧠 Computational Thinking 🐍 Python For Beginners 📐 Algorithm Design 🗃️ Data Structures

Deep Learning Design Patterns

by Andrew Ferlitsch • 2021

Data shift crushed your model? Simple design patterns push accuracy from 10% to 98%.

4.67

🧠 Deep Learning 👁️ Computer Vision 🔄 Data Augmentation 📊 Distribution Shifts 🏭 Production Ml

Deep Learning Design Patterns 91%

Data shift crushed your model? Simple design patterns push accuracy from 10% to 98%.

by Andrew Ferlitsch 2021

4.67

3 ratings

🧠 Deep Learning 👁️ Computer Vision 🔄 Data Augmentation 📊 Distribution Shifts 🏭 Production Ml

The Deep Learning Revolution

by Terrence J. Sejnowski • 2018

The AI that works copies the brain. For decades it was a backwater. Then it won.

3.72

597

🤖 Deep Learning 📜 History Of Ai 🧠 Computational Neuroscience 🎮 Reinforcement Learning 🌐 Unsupervised Learning

The Deep Learning Revolution 91%

The AI that works copies the brain. For decades it was a backwater. Then it won.

by Terrence J. Sejnowski 2018

3.72

597 ratings

🤖 Deep Learning 📜 History Of Ai 🧠 Computational Neuroscience 🎮 Reinforcement Learning 🌐 Unsupervised Learning

Confident Data Skills

by Kirill Eremenko • 2018

From messy data to clean insights to persuasive presentations: the process that lands the promotion.

4.12

211

📊 Data Science 📖 Data Literacy 🤖 Machine Learning Basics 📈 Data Visualization 🧹 Data Preparation

Confident Data Skills 90%

From messy data to clean insights to persuasive presentations: the process that lands the promotion.

by Kirill Eremenko 2018

4.12

211 ratings

📊 Data Science 📖 Data Literacy 🤖 Machine Learning Basics 📈 Data Visualization 🧹 Data Preparation

The Math of Life and Death

by Kit Yates • 2019

Key mathematical ideas govern medicine, law, and media, and your intuition gets each one wrong.

3.90

2k+

The Math of Life and Death 90%

Key mathematical ideas govern medicine, law, and media, and your intuition gets each one wrong.

by Kit Yates 2019

3.90

2k+ ratings

Data Smart

by John W. Foreman • 2013

Real machine learning inside Excel: cluster customers, forecast demand, optimize decisions. No code.

4.12

1k+

📊 Spreadsheet Modeling 📈 Business Analytics 🤖 Machine Learning For Managers 🧮 Quantitative Decision Making 🔮 Forecasting Methods

Data Smart 90%

Real machine learning inside Excel: cluster customers, forecast demand, optimize decisions. No code.

by John W. Foreman 2013

4.12

1k+ ratings

📊 Spreadsheet Modeling 📈 Business Analytics 🤖 Machine Learning For Managers 🧮 Quantitative Decision Making 🔮 Forecasting Methods

Thinking Better

by Marcus du Sautoy • 2021

Mathematical shortcuts that save time, solve problems, and show you what everyone else overlooks.

3.59

618

🧮 Mathematical Thinking 🧠 Mental Shortcuts 🔍 Pattern Recognition ⚙️ Optimization 👁️ Visual Thinking

Thinking Better 90%

Mathematical shortcuts that save time, solve problems, and show you what everyone else overlooks.

by Marcus du Sautoy 2021

3.59

618 ratings

🧮 Mathematical Thinking 🧠 Mental Shortcuts 🔍 Pattern Recognition ⚙️ Optimization 👁️ Visual Thinking

Practical Statistics for Data Scientists

by Peter Bruce • 2020

The statistics data scientists actually use, from EDA to ensembles, with working R and Python code.

4.21

261

📊 Statistical Computing 🔍 Exploratory Data Analysis 📐 Statistical Inference 🔄 Resampling Methods 📈 Regression Modeling

Practical Statistics for Data Scientists Summary

Practical Statistics for Data Scientists 90%

The statistics data scientists actually use, from EDA to ensembles, with working R and Python code.

by Peter Bruce 2020

4.21

261 ratings

📊 Statistical Computing 🔍 Exploratory Data Analysis 📐 Statistical Inference 🔄 Resampling Methods 📈 Regression Modeling

The Alignment Problem

by Brian Christian • 2020

AI learns our blind spots along with our data. Correcting that is the central problem in computing.

4.34

5k+

🎯 Ai Alignment 🤖 Machine Learning Ethics ⚖️ Algorithmic Bias 🔍 Interpretable Ai 🕹️ Reinforcement Learning

The Alignment Problem 90%

AI learns our blind spots along with our data. Correcting that is the central problem in computing.

by Brian Christian 2020

4.34

5k+ ratings

🎯 Ai Alignment 🤖 Machine Learning Ethics ⚖️ Algorithmic Bias 🔍 Interpretable Ai 🕹️ Reinforcement Learning

Robin Hood Math

by Noah Giansiracusa • 2025

Algorithms price your insurance, rank your resume, curate your reality. The math that fights back.

3.91

185

🧮 Algorithmic Literacy 🛡️ Digital Self-Defense 📐 Applied Mathematics 📊 Bayesian Reasoning 📉 Everyday Statistics

Robin Hood Math 90%

Algorithms price your insurance, rank your resume, curate your reality. The math that fights back.

by Noah Giansiracusa 2025

3.91

185 ratings

🧮 Algorithmic Literacy 🛡️ Digital Self-Defense 📐 Applied Mathematics 📊 Bayesian Reasoning 📉 Everyday Statistics

Practicing Trustworthy Machine Learning

by Yada Pruksachatkun • 2023

Privacy, fairness, explainability, robustness: the engineering guide for ML models that earn trust.

4.95

111

🤖 Responsible Ai ⚙️ Ml Engineering ⚖️ Model Fairness 🔍 Explainable Ai 🔒 Privacy-Preserving Ml

Practicing Trustworthy Machine Learning Summary

Practicing Trustworthy Machine Learning 90%

Privacy, fairness, explainability, robustness: the engineering guide for ML models that earn trust.

by Yada Pruksachatkun 2023

4.95

111 ratings

🤖 Responsible Ai ⚙️ Ml Engineering ⚖️ Model Fairness 🔍 Explainable Ai 🔒 Privacy-Preserving Ml

Creativity Code

by Marcus du Sautoy • 2019

AI paints, composes, writes. But can a machine truly be creative? A mathematician investigates.

3.94

2k+

🤖 Machine Creativity 🎨 Ai Generated Art 🖌️ Generative Art 🤔 Philosophy Of Ai 🧠 Cognitive Science

Creativity Code 90%

AI paints, composes, writes. But can a machine truly be creative? A mathematician investigates.

by Marcus du Sautoy 2019

3.94

2k+ ratings

🤖 Machine Creativity 🎨 Ai Generated Art 🖌️ Generative Art 🤔 Philosophy Of Ai 🧠 Cognitive Science

Everyday Chaos

by David Weinberger • 2019

A medical AI diagnoses illness but can't explain how. The age of demanding explanations is over.

3.78

202

🔬 Complexity Science 🔄 Systems Thinking 🤖 Machine Learning 💻 Digital Strategy 🔓 Open Platforms

Everyday Chaos 90%

A medical AI diagnoses illness but can't explain how. The age of demanding explanations is over.

by David Weinberger 2019

3.78

202 ratings

🔬 Complexity Science 🔄 Systems Thinking 🤖 Machine Learning 💻 Digital Strategy 🔓 Open Platforms

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