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🏋️ Model Training

The process of teaching machines to learn from data, covering the iterative cycles of feeding, adjusting, and evaluating that transform raw algorithms into useful intelligence.
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 90%
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
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👁️ Computer Vision
Deep Learning with Python Summary
Deep Learning with Python 90%
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👁️ Computer Vision
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 89%
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 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 89%
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
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 89%
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
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 89%
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
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
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
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 88%
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
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 88%
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
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 88%
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
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 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
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
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 88%
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
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
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
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 88%
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
Build a Large Language Model
by Sebastian Raschka • 2025
Skip expensive pretraining. Build a working LLM from GPT-2 and teach it to follow instructions.
4.60
356
🧠 Large Language Models🗣️ Natural Language Processing🏗️ Transformer Architectures
Build a Large Language Model Summary
Build a Large Language Model 88%
Skip expensive pretraining. Build a working LLM from GPT-2 and teach it to follow instructions.
by Sebastian Raschka 2025
4.60
356 ratings
🧠 Large Language Models🗣️ Natural Language Processing🏗️ Transformer Architectures
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
Hands-On Machine Learning with Scikit-Learn and TensorFlow Summary
Hands-On Machine Learning with Scikit-Learn and TensorFlow 88%
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
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
Machine Learning Simplified Summary
Machine Learning Simplified 88%
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
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
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
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 88%
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
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
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 88%
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
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 88%
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
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
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
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
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
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 88%
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
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
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 87%
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
Java Deep Learning Essentials
by Yusuke Sugomori • 2016
Python demos deep learning; Java deploys it. Architectures and libraries to close the gap.
3.20
5
🧠 Deep Learning☕ Java Machine Learning🔧 Practical Deep Learning
Java Deep Learning Essentials Summary
Java Deep Learning Essentials 87%
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
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 87%
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
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 87%
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
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
The Alignment Problem Summary
The Alignment Problem 87%
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
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 87%
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
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
Practicing Trustworthy Machine Learning Summary
Practicing Trustworthy Machine Learning 87%
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
Understanding Large Language Models
by Thimira Amaratunga • 2023
The 2017 architecture that made LLMs huge and fluent but unable to think, and how it works.
5.00
1
🗣️ Natural Language Processing🤖 Generative Ai📖 Ai Literacy
Understanding Large Language Models Summary
Understanding Large Language Models 87%
The 2017 architecture that made LLMs huge and fluent but unable to think, and how it works.
by Thimira Amaratunga 2023
5.00
1 ratings
🗣️ Natural Language Processing🤖 Generative Ai📖 Ai Literacy
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 87%
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
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
The Deep Learning Revolution Summary
The Deep Learning Revolution 87%
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
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
Apprenticeship Patterns
by Dave Hoover • 2009
Promotion pulls coders away from code. The patterns for staying in the craft while still advancing.
4.10
963
🛠️ Software Craftsmanship🧑‍🏭 Apprenticeship Model🏋️ Deliberate Practice
Apprenticeship Patterns Summary
Apprenticeship Patterns 87%
Promotion pulls coders away from code. The patterns for staying in the craft while still advancing.
by Dave Hoover 2009
4.10
963 ratings
🛠️ Software Craftsmanship🧑‍🏭 Apprenticeship Model🏋️ Deliberate Practice
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 87%
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
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
Artificial Intelligence and Machine Learning for Business Summary
Artificial Intelligence and Machine Learning for Business 87%
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
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 87%
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 87%
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
A Brief History of Artificial Intelligence
by Michael Wooldridge • 2021
AI has overpromised for decades. Deep learning is different, but not how most think.
3.87
555
📜 Ai History🧠 Machine Learning⚖️ Ai Ethics
A Brief History of Artificial Intelligence Summary
A Brief History of Artificial Intelligence 87%
AI has overpromised for decades. Deep learning is different, but not how most think.
by Michael Wooldridge 2021
3.87
555 ratings
📜 Ai History🧠 Machine Learning⚖️ Ai Ethics
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⭐
⭐
⭐
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