Themes Lists Trending New
Start free trial
EnglishEnglish
EspañolSpanish
简体中文Chinese
繁體中文Chinese (Traditional)
FrançaisFrench
DeutschGerman
日本語Japanese
PortuguêsPortuguese
ItalianoItalian
한국어Korean
РусскийRussian
NederlandsDutch
العربيةArabic
PolskiPolish
हिन्दीHindi
Tiếng ViệtVietnamese
SvenskaSwedish
ΕλληνικάGreek
TürkçeTurkish
ไทยThai
ČeštinaCzech
RomânăRomanian
MagyarHungarian
УкраїнськаUkrainian
IndonesiaIndonesian
DanskDanish
SuomiFinnish
БългарскиBulgarian
עבריתHebrew
NorskNorwegian
HrvatskiCroatian
CatalàCatalan
SlovenčinaSlovak
LietuviųLithuanian
SlovenščinaSlovenian
СрпскиSerbian
EestiEstonian
LatviešuLatvian
فارسیPersian
മലയാളംMalayalam
தமிழ்Tamil
اردوUrdu
SoBrief
Searching...

🕸️ Graphical Models

Books on probabilistic graphical models that represent complex systems of variables and dependencies, bridging statistics, machine learning, and reasoning under uncertainty.
Graph Databases
by Ian Robinson • 2013
Relational databases fail on connected data. Graph databases traverse deep links in milliseconds.
3.64
437
🕸️ Graph Databases🗄️ Nosql Databases📐 Graph Theory
Graph Databases Summary
Graph Databases 89%
Relational databases fail on connected data. Graph databases traverse deep links in milliseconds.
by Ian Robinson 2013
3.64
437 ratings
🕸️ Graph Databases🗄️ Nosql Databases📐 Graph Theory
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
Introduction To Machine Learning Summary
Introduction To Machine Learning 88%
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
Practical Statistics for Data Scientists
by Peter Bruce • 2017
The statistical methods data scientists use daily, from boxplots to bootstrap, minus the proofs.
4.02
545
🛠️ Practical Data Science📈 Applied Statistics🔍 Exploratory Data Analysis
Practical Statistics for Data Scientists Summary
Practical Statistics for Data Scientists 88%
The statistical methods data scientists use daily, from boxplots to bootstrap, minus the proofs.
by Peter Bruce 2017
4.02
545 ratings
🛠️ Practical Data Science📈 Applied Statistics🔍 Exploratory Data Analysis
Learning Python Data Visualization
by Chad Adams • 2014
Turn spreadsheets and web data into SVG charts with Python, no design background required.
3.00
5
📊 Data Visualization🐍 Python Programming📈 Chart Creation
Learning Python Data Visualization Summary
Learning Python Data Visualization 88%
Turn spreadsheets and web data into SVG charts with Python, no design background required.
by Chad Adams 2014
3.00
5 ratings
📊 Data Visualization🐍 Python Programming📈 Chart Creation
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
The Elements of Statistical Learning Summary
The Elements of Statistical Learning 87%
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
Learning OpenCV
by Gary Bradski • 2008
From smoothing to machine learning: the complete OpenCV toolkit for building computer vision apps.
4.01
171
🖥️ Computer Vision🌄 Image Processing📚 Open Source Libraries
Learning OpenCV Summary
Learning OpenCV 87%
From smoothing to machine learning: the complete OpenCV toolkit for building computer vision apps.
by Gary Bradski 2008
4.01
171 ratings
🖥️ Computer Vision🌄 Image Processing📚 Open Source Libraries
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
Practical Statistics for Data Scientists Summary
Practical Statistics for Data Scientists 87%
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
The Nature of Code
by Daniel Shiffman • 2012
Code that breathes: how to build simulations that move, think, and evolve on your screen.
4.57
502
🎨 Creative Coding🖼️ Generative Art🟩 Cellular Automata
The Nature of Code Summary
The Nature of Code 87%
Code that breathes: how to build simulations that move, think, and evolve on your screen.
by Daniel Shiffman 2012
4.57
502 ratings
🎨 Creative Coding🖼️ Generative Art🟩 Cellular Automata
The Book of Why
by Judea Pearl • 2018
Data can't tell you why. A mathematical science of cause and effect finally can.
3.93
7k+
🏹 Causal Inference🔄 Counterfactuals📉 Limits Of Correlation
The Book of Why Summary
The Book of Why 87%
Data can't tell you why. A mathematical science of cause and effect finally can.
by Judea Pearl 2018
3.93
7k+ ratings
🏹 Causal Inference🔄 Counterfactuals📉 Limits Of Correlation
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
Machine Learning with R Summary
Machine Learning with R 87%
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
Visualizing Mathematics with 3D Printing
by Henry Segerman • 2016
3D printing turns polyhedra, knots, and 4D shadows into hands-on objects you finally grasp.
4.08
13
🖨️ 3d Printing🧮 Mathematical Models🌌 Higher Dimensions
Visualizing Mathematics with 3D Printing Summary
Visualizing Mathematics with 3D Printing 87%
3D printing turns polyhedra, knots, and 4D shadows into hands-on objects you finally grasp.
by Henry Segerman 2016
4.08
13 ratings
🖨️ 3d Printing🧮 Mathematical Models🌌 Higher Dimensions
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
Machine Learning For Absolute Beginners Summary
Machine Learning For Absolute Beginners 87%
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
Nonlinear Dynamics and Chaos
by Steven H. Strogatz • 1994
How simple rules produce unpredictable motion, and the pictures that reveal the hidden order.
4.38
2k+
🌀 Nonlinear Dynamics🕸️ Complex Systems📊 Mathematical Modeling
Nonlinear Dynamics and Chaos Summary
Nonlinear Dynamics and Chaos 87%
How simple rules produce unpredictable motion, and the pictures that reveal the hidden order.
by Steven H. Strogatz 1994
4.38
2k+ ratings
🌀 Nonlinear Dynamics🕸️ Complex Systems📊 Mathematical Modeling
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
Deep Learning with Python Summary
Deep Learning with Python 87%
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
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
The Little Book of Deep Learning Summary
The Little Book of Deep Learning 87%
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
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
5
📊 Data Science🤖 Machine Learning🔍 Exploratory Data Analysis
Python Machine Learning Case Studies Summary
Python Machine Learning Case Studies 87%
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
Fundamentals of Digital Image Processing
by Anil K. Jain • 1988
From pixel to picture: the math that samples, restores, compresses, and reconstructs digital images.
3.98
145
🖼️ Image Processing📡 Signal Processing〰️ Fourier Analysis
Fundamentals of Digital Image Processing Summary
Fundamentals of Digital Image Processing 87%
From pixel to picture: the math that samples, restores, compresses, and reconstructs digital images.
by Anil K. Jain 1988
3.98
145 ratings
🖼️ Image Processing📡 Signal Processing〰️ Fourier Analysis
Small Worlds
by Duncan J. Watts • 1999
A few distant links turn clustered networks into superhighways for disease, ideas, and synchrony.
3.88
85
🕸️ Network Science📐 Graph Theory🔗 Complex Systems
Small Worlds Summary
Small Worlds 87%
A few distant links turn clustered networks into superhighways for disease, ideas, and synchrony.
by Duncan J. Watts 1999
3.88
85 ratings
🕸️ Network Science📐 Graph Theory🔗 Complex Systems
Think Stats
by Allen B. Downey • 2011
Statistics taught through code: why simulation and real data beat memorization every time.
3.64
469
💻 Computational Statistics🔍 Exploratory Data Analysis🐍 Python Data Analysis
Think Stats Summary
Think Stats 87%
Statistics taught through code: why simulation and real data beat memorization every time.
by Allen B. Downey 2011
3.64
469 ratings
💻 Computational Statistics🔍 Exploratory Data Analysis🐍 Python Data Analysis
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
64
📈 Time Series Analysis🔧 Feature Engineering🧹 Data Preparation
Practical Time Series Analysis Summary
Practical Time Series Analysis 87%
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
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
The Hundred-Page Machine Learning Book Summary
The Hundred-Page Machine Learning Book 87%
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
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
Python Data Science Handbook Summary
Python Data Science Handbook 87%
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
Unfolding the Napkin
by Dan Roam • 2009
Turn any business mess into a picture everyone gets, with the drawing skills you already have.
4.04
964
👁️ Visual Thinking✍️ Hand-Drawn Visuals🖍️ Graphic Facilitation
Unfolding the Napkin Summary
Unfolding the Napkin 87%
Turn any business mess into a picture everyone gets, with the drawing skills you already have.
by Dan Roam 2009
4.04
964 ratings
👁️ Visual Thinking✍️ Hand-Drawn Visuals🖍️ Graphic Facilitation
Deep Learning Design Patterns
by Andrew Ferlitsch • 2021
Data shift crushed your model? Simple design patterns push accuracy from 10% to 98%.
4.67
3
🧠 Deep Learning👁️ Computer Vision🔄 Data Augmentation
Deep Learning Design Patterns Summary
Deep Learning Design Patterns 87%
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
Love Triangle
by Matt Parker • 2024
Triangles build skyscrapers, animate movies, and decode sound: the shape that runs the world.
3.93
2k+
🔢 Popular Mathematics📐 Geometry🎨 Art And Mathematics
Love Triangle Summary
Love Triangle 87%
Triangles build skyscrapers, animate movies, and decode sound: the shape that runs the world.
by Matt Parker 2024
3.93
2k+ ratings
🔢 Popular Mathematics📐 Geometry🎨 Art And Mathematics
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
Fundamentals of Machine Learning for Predictive Data Analytics Summary
Fundamentals of Machine Learning for Predictive Data Analytics 87%
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
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
1
🧠 Machine Learning🧬 Deep Learning🔗 Neural Networks
Neural Network for Beginners Summary
Neural Network for Beginners 87%
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
Python for Data Analysis
by Wes McKinney • 2011
The pandas creator teaches the full Python data pipeline: messy files in, statistical models out.
4.17
2k+
🧹 Data Wrangling🔬 Scientific Computing📊 Data Visualization
Python for Data Analysis Summary
Python for Data Analysis 87%
The pandas creator teaches the full Python data pipeline: messy files in, statistical models out.
by Wes McKinney 2011
4.17
2k+ ratings
🧹 Data Wrangling🔬 Scientific Computing📊 Data Visualization
Python for Data Analysis
by Oscar Scratch • 2019
Python data analysis, taught through questions: NumPy, Pandas, and the bridge to machine learning.
3.50
2
🧮 Scientific Computing🔄 Data Manipulation📊 Data Visualization
Python for Data Analysis Summary
Python for Data Analysis 87%
Python data analysis, taught through questions: NumPy, Pandas, and the bridge to machine learning.
by Oscar Scratch 2019
3.50
2 ratings
🧮 Scientific Computing🔄 Data Manipulation📊 Data Visualization
Low-Code AI
by Gwendolyn Stripling • 2023
Skip Python. Train regression models, engineer features, and explain predictions, all in SQL.
4.33
6
🛠️ Practical Ml📊 Data Exploration🔧 Feature Engineering
Low-Code AI Summary
Low-Code AI 87%
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
Storytelling with Data
by Cole Nussbaumer Knaflic • 2019
Turn chart clutter into clear stories. Practice exercises that make your data impossible to ignore.
4.47
179
📊 Data Visualization💼 Business Presentations📖 Visual Storytelling
Storytelling with Data Summary
Storytelling with Data 87%
Turn chart clutter into clear stories. Practice exercises that make your data impossible to ignore.
by Cole Nussbaumer Knaflic 2019
4.47
179 ratings
📊 Data Visualization💼 Business Presentations📖 Visual Storytelling
Doing Data Science
by Cathy O'Neil • 2013
Your model is lying to you. The ninety percent of data science that algorithms won't fix.
3.73
567
📊 Data Science📈 Statistical Thinking🧹 Data Wrangling
Doing Data Science Summary
Doing Data Science 87%
Your model is lying to you. The ninety percent of data science that algorithms won't fix.
by Cathy O'Neil 2013
3.73
567 ratings
📊 Data Science📈 Statistical Thinking🧹 Data Wrangling
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
Algorithms of the Intelligent Web Summary
Algorithms of the Intelligent Web 87%
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
Shape
by Jordan Ellenberg • 2021
Geometry is not about triangles. It is the hidden structure of pandemics, search, and democracy.
3.73
2k+
🧮 Popular Mathematics🔗 Network Theory🎲 Randomness And Probability
Shape Summary
Shape 86%
Geometry is not about triangles. It is the hidden structure of pandemics, search, and democracy.
by Jordan Ellenberg 2021
3.73
2k+ ratings
🧮 Popular Mathematics🔗 Network Theory🎲 Randomness And Probability
The Theory That Would Not Die
by Sharon Bertsch McGrayne • 2011
Statisticians said it was dead. Turing used it to crack Enigma. Computers made it unstoppable.
3.77
3k+
🧮 Bayesian Statistics📜 History Of Mathematics🎲 Probability Theory
The Theory That Would Not Die Summary
The Theory That Would Not Die 86%
Statisticians said it was dead. Turing used it to crack Enigma. Computers made it unstoppable.
by Sharon Bertsch McGrayne 2011
3.77
3k+ ratings
🧮 Bayesian Statistics📜 History Of Mathematics🎲 Probability Theory
Predictive Analytics For Dummies
by Anasse Bari • 2013
A guide to building models that forecast, classify, and find hidden patterns, without a math degree.
3.74
111
📊 Data Science🔮 Predictive Modeling🐥 Beginner Guides
Predictive Analytics For Dummies Summary
Predictive Analytics For Dummies 86%
A guide to building models that forecast, classify, and find hidden patterns, without a math degree.
by Anasse Bari 2013
3.74
111 ratings
📊 Data Science🔮 Predictive Modeling🐥 Beginner Guides
Grokking Algorithms An Illustrated Guide For Programmers and Other Curious People
by Aditya Y. Bhargava • 2015
Algorithms stripped of dense math: a hand-drawn guide to thinking in runtimes and data structures.
4.41
5k+
🔢 Algorithm Fundamentals🧱 Data Structures🔍 Sorting And Searching
Grokking Algorithms An Illustrated Guide For Programmers and Other Curious People Summary
Grokking Algorithms An Illustrated Guide For Programmers and Other Curious People 86%
Algorithms stripped of dense math: a hand-drawn guide to thinking in runtimes and data structures.
by Aditya Y. Bhargava 2015
4.41
5k+ ratings
🔢 Algorithm Fundamentals🧱 Data Structures🔍 Sorting And Searching
The Algorithm Design Manual
by Steven S. Skiena • 1997
The first step is modeling, not coding. A practical manual and its 75-problem catalog show how.
4.34
3k+
🧩 Algorithm Design🗃️ Data Structures🕸️ Graph Algorithms
The Algorithm Design Manual Summary
The Algorithm Design Manual 86%
The first step is modeling, not coding. A practical manual and its 75-problem catalog show how.
by Steven S. Skiena 1997
4.34
3k+ ratings
🧩 Algorithm Design🗃️ Data Structures🕸️ Graph Algorithms
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
Algorithms Summary
Algorithms 86%
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
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
AI and Machine Learning for Coders Summary
AI and Machine Learning for Coders 86%
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
Curso Diseño Gráfico
by Anna María López López • 2013
Every technical step of graphic design, from brief to bleed, in one complete professional course.
4.18
17
🎨 Graphic Design👁️ Visual Communication🌈 Color Theory
Curso Diseño Gráfico Summary
Curso Diseño Gráfico 86%
Every technical step of graphic design, from brief to bleed, in one complete professional course.
by Anna María López López 2013
4.18
17 ratings
🎨 Graphic Design👁️ Visual Communication🌈 Color Theory
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
Neural Networks, Fuzzy Logic And Genetic Algorithms Summary
Neural Networks, Fuzzy Logic And Genetic Algorithms 86%
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
Statistics 101
by David Borman • 2018
A single-volume stats class: summarize data, test hunches, and build forecasts, minus the jargon.
2.94
147
📊 Introductory Statistics📈 Data Analysis🧐 Statistical Literacy
Statistics 101 Summary
Statistics 101 86%
A single-volume stats class: summarize data, test hunches, and build forecasts, minus the jargon.
by David Borman 2018
2.94
147 ratings
📊 Introductory Statistics📈 Data Analysis🧐 Statistical Literacy
The Art of Statistics
by David Spiegelhalter • 2019
Numbers are mute. How statisticians make them speak, and why p-values and correlation aren't enough.
4.15
6k+
🧮 Statistical Literacy🔗 Causal Inference🎲 Bayesian Methods
The Art of Statistics Summary
The Art of Statistics 86%
Numbers are mute. How statisticians make them speak, and why p-values and correlation aren't enough.
by David Spiegelhalter 2019
4.15
6k+ ratings
🧮 Statistical Literacy🔗 Causal Inference🎲 Bayesian Methods
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
Deep Learning Summary
Deep Learning 86%
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
Keras Reinforcement Learning Projects
by Giuseppe Ciaburro • 2018
Nine Keras projects that bring reinforcement learning from theory to working self-learning agents.
4.00
1
🤖 Reinforcement Learning🧠 Deep Learning🔗 Neural Networks
Keras Reinforcement Learning Projects Summary
Keras Reinforcement Learning Projects 86%
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
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
AIQ Summary
AIQ 86%
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
Information Is Beautiful
by David McCandless • 2001
Concept is the secret: why a simple, clever data drawing can reveal more than a supercomputer.
4.12
4k+
📊 Data Visualization🎨 Data Art👁️ Visual Literacy
Information Is Beautiful Summary
Information Is Beautiful 86%
Concept is the secret: why a simple, clever data drawing can reveal more than a supercomputer.
by David McCandless 2001
4.12
4k+ ratings
📊 Data Visualization🎨 Data Art👁️ Visual Literacy
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
Machine Learning for Dummies Summary
Machine Learning for Dummies 86%
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
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
Creativity Code Summary
Creativity Code 86%
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
Home
Search
Swipe
Library
Get App
Try Full Access for 3 Days
Listen, bookmark, and more
Compare Features Free Pro
📖 Read Summaries
Read unlimited summaries. Free users get 3 per month
🎧 Listen to Summaries
Listen to unlimited summaries in 40 languages
 —
❤️ Unlimited Bookmarks
Free users are limited to 4
 —
📜 Unlimited History
Free users are limited to 4
 —
📥 Unlimited Downloads
Free users are limited to 1
 —
Risk-Free Timeline
Today: Get Instant Access
Listen to full summaries of 26,000+ books. That's 12,000+ hours of audio!
Day 2: Trial Reminder
We'll send you a notification that your trial is ending soon.
Day 3: Your subscription begins
You'll be charged on Jul 25,
cancel anytime before.
Consume 2.8× More Books
2.8× more books Listening Reading
Our users love us
600,000+ readers
Trustpilot Rating
TrustPilot
4.6 Excellent
This site is a total game-changer. I've been flying through book summaries like never before. Highly, highly recommend.
— Dave G
Worth my money and time, and really well made. I've never seen this quality of summaries on other websites. Very helpful!
— Em
Highly recommended!! Fantastic service. Perfect for those that want a little more than a teaser but not all the intricate details of a full audio book.
— Greg M
Save 62%
Yearly
$119.88 $44.99/year/yr
$3.75/mo
Monthly
$9.99/mo
Start a 3-Day Free Trial
3 days free, then $44.99/year. Cancel anytime.
Unlock a world of fiction & nonfiction books
26,000+ books for the price of 2 books
Read any book in 10 minutes
Discover new books like Tinder
Request any book if it's not summarized
Read more books than anyone you know
#1 app for book lovers
Lifelike & immersive summaries
30-day money-back guarantee
Download summaries in EPUBs or PDFs
Cancel anytime in a few clicks
Scanner
Find a barcode to scan

⭐
⭐
⭐
We have a special gift for you
Open
38% OFF
DISCOUNT FOR YOU
⭐
⭐
⭐
$79.99
$49.99/year
only $4.16 per month
Continue
2 taps to start, super easy to cancel
Settings
General
Widget
Loading...
⭐
⭐
⭐
We have a special gift for you
Open
38% OFF
DISCOUNT FOR YOU
⭐
⭐
⭐
$79.99
$49.99/year
only $4.16 per month
Continue
2 taps to start, super easy to cancel