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🔄 Data Augmentation

Techniques for expanding and enriching training datasets, a critical practice in machine learning that improves model performance when real-world data is scarce.
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📊 Distribution Shifts
Deep Learning Design Patterns Summary
Deep Learning Design Patterns 90%
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📊 Distribution Shifts
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 89%
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
AI for Data Science
by Zacharias Voulgaris • 2018
The real AI toolkit goes beyond deep learning: optimization, fuzzy logic, ensembles.
4.55
20
📊 Data Science🧠 Deep Learning⚙️ Optimization Algorithms
AI for Data Science Summary
AI for Data Science 89%
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
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 89%
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
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 89%
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
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 89%
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
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 89%
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
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
Introduction to Machine Learning with Python Summary
Introduction to Machine Learning with Python 89%
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
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
Confident Data Skills Summary
Confident Data Skills 88%
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
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 88%
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
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 88%
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
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
Machine Learning For Absolute Beginners Summary
Machine Learning For Absolute Beginners 88%
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
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 88%
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
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 88%
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
Machine Learning
by Dr Ruchi Doshi • 2021
From training models with labeled data to finding hidden patterns: the algorithms behind modern AI.
5.00
1
🧠 Machine Learning📊 Supervised Learning🧬 Deep Learning
Machine Learning Summary
Machine Learning 88%
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
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 88%
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
How to AI
by Christopher Mims • 2026
How to delegate the boring parts to AI without ever trusting the output.
3.77
111
📖 Ai Literacy🤝 Ai Augmentation🤖 Generative Ai
How to AI Summary
How to AI 88%
How to delegate the boring parts to AI without ever trusting the output.
by Christopher Mims 2026
3.77
111 ratings
📖 Ai Literacy🤝 Ai Augmentation🤖 Generative Ai
Artificial Intelligence Basics
by Tom Taulli • 2019
AI without the math: what machine learning does and where automation fits in your business.
3.50
210
🧠 Ai Fundamentals🏭 Ai Adoption🔄 Digital Transformation
Artificial Intelligence Basics Summary
Artificial Intelligence Basics 88%
AI without the math: what machine learning does and where automation fits in your business.
by Tom Taulli 2019
3.50
210 ratings
🧠 Ai Fundamentals🏭 Ai Adoption🔄 Digital Transformation
Python for Geeks
by Muhammad Asif • 2021
Machine learning from notebook to production: Python libraries, data prep, and deployment paths.
4.50
8
🐍 Python Programming⚙️ Machine Learning Engineering📊 Data Science
Python for Geeks Summary
Python for Geeks 88%
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
Data Strategy
by Bernard Marr • 2017
Profit from the data firehose: pick the right data, build a company that acts on it.
3.77
418
📊 Data Strategy📈 Business Intelligence💾 Big Data
Data Strategy Summary
Data Strategy 88%
Profit from the data firehose: pick the right data, build a company that acts on it.
by Bernard Marr 2017
3.77
418 ratings
📊 Data Strategy📈 Business Intelligence💾 Big Data
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 88%
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
Big Data
by Viktor Mayer-Schönberger • 2013
The era of sampling, clean data, and causal certainty is over. What replaces it is stranger.
3.69
9k+
💰 Data As Asset📈 Predictive Analytics🧹 Imperfect Data
Big Data Summary
Big Data 88%
The era of sampling, clean data, and causal certainty is over. What replaces it is stranger.
by Viktor Mayer-Schönberger 2013
3.69
9k+ ratings
💰 Data As Asset📈 Predictive Analytics🧹 Imperfect Data
Data Science
by John D. Kelleher • 2018
Turning raw data into decisions requires a defined process, not just algorithms and statistics.
3.90
876
🔎 Data Mining🧭 Data Science Methodology📈 Predictive Modeling
Data Science Summary
Data Science 88%
Turning raw data into decisions requires a defined process, not just algorithms and statistics.
by John D. Kelleher 2018
3.90
876 ratings
🔎 Data Mining🧭 Data Science Methodology📈 Predictive Modeling
What Are ChatGPT and Its Friends?
by Mike Loukides • 2023
A field guide to large language models: surprising strengths, dangerous blind spots, and real costs.
4.00
7
🧬 Generative Ai🤖 Large Language Models⚖️ Ai Ethics
What Are ChatGPT and Its Friends? Summary
What Are ChatGPT and Its Friends? 88%
A field guide to large language models: surprising strengths, dangerous blind spots, and real costs.
by Mike Loukides 2023
4.00
7 ratings
🧬 Generative Ai🤖 Large Language Models⚖️ Ai Ethics
The AI Playbook
by Eric Siegel • 2024
How to get machine learning out of the lab: sell the operational improvement, not the algorithm.
3.98
127
🏢 Enterprise Technology🤖 Applied Ai🔄 Change Management
The AI Playbook Summary
The AI Playbook 88%
How to get machine learning out of the lab: sell the operational improvement, not the algorithm.
by Eric Siegel 2024
3.98
127 ratings
🏢 Enterprise Technology🤖 Applied Ai🔄 Change Management
Data Science for Business
by Foster Provost • 2013
Why overfitting sinks most data projects, and the conceptual tools that stop it.
4.13
3k+
📊 Business Analytics⛏️ Data Mining📏 Model Evaluation
Data Science for Business Summary
Data Science for Business 88%
Why overfitting sinks most data projects, and the conceptual tools that stop it.
by Foster Provost 2013
4.13
3k+ ratings
📊 Business Analytics⛏️ Data Mining📏 Model Evaluation
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 88%
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
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
Numsense! Data Science for the Layman Summary
Numsense! Data Science for the Layman 88%
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
Why Data Science Projects Fail
by Douglas Gray • 2024
Eighty percent of AI projects fail. The models work fine; the people, data, and expectations don't.
5.00
19
📊 Data Science Management🤖 Ai Implementation⚙️ Mlops
Why Data Science Projects Fail Summary
Why Data Science Projects Fail 88%
Eighty percent of AI projects fail. The models work fine; the people, data, and expectations don't.
by Douglas Gray 2024
5.00
19 ratings
📊 Data Science Management🤖 Ai Implementation⚙️ Mlops
Fundamentals of Data Engineering
by Joe Reis • 2022
Data scientists spend 80% of their time cleaning data. The systems blueprint that frees them.
4.16
945
🛠️ Data Engineering🏗️ Data Architecture🔗 Data Pipelines
Fundamentals of Data Engineering Summary
Fundamentals of Data Engineering 88%
Data scientists spend 80% of their time cleaning data. The systems blueprint that frees them.
by Joe Reis 2022
4.16
945 ratings
🛠️ Data Engineering🏗️ Data Architecture🔗 Data Pipelines
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
Data Science from Scratch Summary
Data Science from Scratch 88%
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
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 88%
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
Natural Language Processing with Transformers
by Lewis Tunstall • 2022
Build NLP applications with the open-source stack that turned transformer research practical.
4.39
211
🗣️ Natural Language Processing🧠 Deep Learning🤖 Transformers
Natural Language Processing with Transformers Summary
Natural Language Processing with Transformers 88%
Build NLP applications with the open-source stack that turned transformer research practical.
by Lewis Tunstall 2022
4.39
211 ratings
🗣️ Natural Language Processing🧠 Deep Learning🤖 Transformers
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 88%
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
AI and Machine Learning for On-Device Development
by Laurence Moroney • 2021
Privacy-respecting on-device AI: face detection, text analysis, custom models. No cloud, no PhD.
4.17
6
📱 Mobile Development🧠 On-Device Ai🤖 Applied Machine Learning
AI and Machine Learning for On-Device Development Summary
AI and Machine Learning for On-Device Development 88%
Privacy-respecting on-device AI: face detection, text analysis, custom models. No cloud, no PhD.
by Laurence Moroney 2021
4.17
6 ratings
📱 Mobile Development🧠 On-Device Ai🤖 Applied Machine Learning
Superagency
by Reid Hoffman • 2025
AI multiplies human agency. That power will concentrate or spread. The choice is ours.
3.33
1k+
🏛️ Ai Policy🌅 Tech Optimism⚖️ Ai Ethics
Superagency Summary
Superagency 88%
AI multiplies human agency. That power will concentrate or spread. The choice is ours.
by Reid Hoffman 2025
3.33
1k+ ratings
🏛️ Ai Policy🌅 Tech Optimism⚖️ Ai Ethics
Artificial Intelligence (WIRED guides)
by Matthew Burgess • 2021
AI masters chess, spots cancer, drives cars. But who trains it, and on whose data?
3.71
147
🖥️ Machine Learning🧠 Deep Learning⚖️ Ai Ethics
Artificial Intelligence (WIRED guides) Summary
Artificial Intelligence (WIRED guides) 88%
AI masters chess, spots cancer, drives cars. But who trains it, and on whose data?
by Matthew Burgess 2021
3.71
147 ratings
🖥️ Machine Learning🧠 Deep Learning⚖️ Ai Ethics
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 88%
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
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
The Master Algorithm Summary
The Master Algorithm 88%
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
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 88%
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
AI Engineering
by Chip Huyen • 2025
Stop training models from scratch. The new discipline for building AI that ships.
4.37
1k+
🏗️ Llm Application Development📝 Prompt Engineering🔍 Rag Systems
AI Engineering Summary
AI Engineering 88%
Stop training models from scratch. The new discipline for building AI that ships.
by Chip Huyen 2025
4.37
1k+ ratings
🏗️ Llm Application Development📝 Prompt Engineering🔍 Rag Systems
All-in On AI
by Thomas H. Davenport • 2023
Less than one percent of large companies are built around AI. The playbook for the rest.
3.23
273
🤖 Ai Adoption💻 Digital Transformation🎯 Corporate Strategy
All-in On AI Summary
All-in On AI 88%
Less than one percent of large companies are built around AI. The playbook for the rest.
by Thomas H. Davenport 2023
3.23
273 ratings
🤖 Ai Adoption💻 Digital Transformation🎯 Corporate Strategy
Applied Artificial Intelligence
by Mariya Yao • 2018
Deploy AI that actually works: a playbook for data, talent, ethics, and the metrics that matter.
3.32
93
🏢 Enterprise Ai🔄 Digital Transformation🧹 Data Quality
Applied Artificial Intelligence Summary
Applied Artificial Intelligence 88%
Deploy AI that actually works: a playbook for data, talent, ethics, and the metrics that matter.
by Mariya Yao 2018
3.32
93 ratings
🏢 Enterprise Ai🔄 Digital Transformation🧹 Data Quality
Hadoop
by Tom White • 2009
How to turn cheap servers into a petabyte-scale data platform, from HDFS to real-time streaming.
3.93
1k+
📊 Big Data🖧 Distributed Systems🐘 Hadoop Ecosystem
Hadoop Summary
Hadoop 88%
How to turn cheap servers into a petabyte-scale data platform, from HDFS to real-time streaming.
by Tom White 2009
3.93
1k+ ratings
📊 Big Data🖧 Distributed Systems🐘 Hadoop Ecosystem
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
Machine Learning Summary
Machine Learning 88%
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
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 88%
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
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 88%
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
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
Designing Machine Learning Systems Summary
Designing Machine Learning Systems 88%
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
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 88%
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
Real World AI
by Alyssa Simpson Rochwerger • 2021
Bring AI into a real business without bias, drift, and wasted millions: the practical playbook.
4.01
88
🏢 Enterprise Ai🎯 Ai Strategy⚖️ Responsible Ai
Real World AI Summary
Real World AI 88%
Bring AI into a real business without bias, drift, and wasted millions: the practical playbook.
by Alyssa Simpson Rochwerger 2021
4.01
88 ratings
🏢 Enterprise Ai🎯 Ai Strategy⚖️ Responsible Ai
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