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📝 Text Classification

Technical explorations of algorithms and models that automatically categorize documents, from spam filtering to sentiment analysis, at the intersection of NLP and 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 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
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 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 88%
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
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
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
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
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
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 87%
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
Everything Is Miscellaneous
by David Weinberger • 2007
Atoms forced one shelf per book. Bits let every fact live in many places at once.
3.74
2k+
📐 Information Architecture🏷️ Folksonomies🗂️ Classification Systems
Everything Is Miscellaneous Summary
Everything Is Miscellaneous 87%
Atoms forced one shelf per book. Bits let every fact live in many places at once.
by David Weinberger 2007
3.74
2k+ ratings
📐 Information Architecture🏷️ Folksonomies🗂️ Classification Systems
Organising Knowledge
by Patrick Lambe • 2007
Fragmented knowledge kills organizations. A shared taxonomy, built right, brings them back together.
3.95
64
🧠 Knowledge Management🗂️ Taxonomy Development🏛️ Information Architecture
Organising Knowledge Summary
Organising Knowledge 87%
Fragmented knowledge kills organizations. A shared taxonomy, built right, brings them back together.
by Patrick Lambe 2007
3.95
64 ratings
🧠 Knowledge Management🗂️ Taxonomy Development🏛️ Information Architecture
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 87%
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 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 87%
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
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 87%
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
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
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
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
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 87%
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
The Bestseller Code
by Jodie Archer • 2016
An algorithm spots bestsellers with 80 percent accuracy, reading signals no writing class teaches.
3.81
1k+
✍️ Novel Writing📊 Text Mining📈 Plot Structure
The Bestseller Code Summary
The Bestseller Code 87%
An algorithm spots bestsellers with 80 percent accuracy, reading signals no writing class teaches.
by Jodie Archer 2016
3.81
1k+ ratings
✍️ Novel Writing📊 Text Mining📈 Plot Structure
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
Linguistic Fingerprints
by Roger J. Kreuz • 2023
The hidden patterns in your words identify you better than fingerprints: stylometry reads them.
3.50
20
🗣️ Linguistic Identity📊 Stylometry🔍 Forensic Linguistics
Linguistic Fingerprints Summary
Linguistic Fingerprints 87%
The hidden patterns in your words identify you better than fingerprints: stylometry reads them.
by Roger J. Kreuz 2023
3.50
20 ratings
🗣️ Linguistic Identity📊 Stylometry🔍 Forensic Linguistics
Mastering Regular Expressions
by Jeffrey E.F. Friedl • 1997
Understand the engine behind your regex: why some patterns crawl, and how to make them run.
4.16
2k+
🧩 Regular Expressions📝 Text Processing🔍 Pattern Matching
Mastering Regular Expressions Summary
Mastering Regular Expressions 87%
Understand the engine behind your regex: why some patterns crawl, and how to make them run.
by Jeffrey E.F. Friedl 1997
4.16
2k+ ratings
🧩 Regular Expressions📝 Text Processing🔍 Pattern Matching
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 87%
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
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
Content Strategy for the Web
by Kristina Halvorson • 2012
Everyone demands new web content. Nobody plans for its upkeep. The system that changes that.
4.00
3k+
🧱 Content Strategy✍️ Web Writing♻️ Content Lifecycle
Content Strategy for the Web Summary
Content Strategy for the Web 87%
Everyone demands new web content. Nobody plans for its upkeep. The system that changes that.
by Kristina Halvorson 2012
4.00
3k+ ratings
🧱 Content Strategy✍️ Web Writing♻️ Content Lifecycle
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 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
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 87%
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
The Elements of Content Strategy
by Erin Kissane • 2011
Great web content does not just happen. The discipline, workflow, and standards for planning it.
3.73
2k+
🧩 Content Strategy📝 Web Writing🧑‍💻 User-Centered Design
The Elements of Content Strategy Summary
The Elements of Content Strategy 87%
Great web content does not just happen. The discipline, workflow, and standards for planning it.
by Erin Kissane 2011
3.73
2k+ ratings
🧩 Content Strategy📝 Web Writing🧑‍💻 User-Centered Design
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 87%
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
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
Everyday Chaos Summary
Everyday Chaos 87%
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
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 87%
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 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 87%
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
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 87%
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
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
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 87%
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
The Secret Life of Pronouns
by James W. Pennebaker • 2011
Your pronouns betray who you are: your status, your emotions, even whether you're lying.
3.67
3k+
🧠 Psycholinguistics📊 Text Analysis🕵️ Deception Detection
The Secret Life of Pronouns Summary
The Secret Life of Pronouns 86%
Your pronouns betray who you are: your status, your emotions, even whether you're lying.
by James W. Pennebaker 2011
3.67
3k+ ratings
🧠 Psycholinguistics📊 Text Analysis🕵️ Deception Detection
A World Without "Whom"
by Emmy J. Favilla • 2017
The internet changed English. Here is the style guide that keeps up.
3.72
491
📖 Style Guides🌐 Internet Linguistics🔄 Language Evolution
A World Without "Whom" Summary
A World Without "Whom" 86%
The internet changed English. Here is the style guide that keeps up.
by Emmy J. Favilla 2017
3.72
491 ratings
📖 Style Guides🌐 Internet Linguistics🔄 Language Evolution
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 86%
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
Rise of Generative AI and ChatGPT
by Utpal Chakraborty • 2023
Generative AI's business playbook: what ChatGPT delivers, where it stumbles, and what comes next.
1.33
12
🧠 Generative Ai💼 Ai In Business⚖️ Ai Ethics
Rise of Generative AI and ChatGPT Summary
Rise of Generative AI and ChatGPT 86%
Generative AI's business playbook: what ChatGPT delivers, where it stumbles, and what comes next.
by Utpal Chakraborty 2023
1.33
12 ratings
🧠 Generative Ai💼 Ai In Business⚖️ Ai Ethics
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 86%
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
Artificial Intelligence in Practice
by Bernard Marr • 2019
Robots patrol Walmart aisles. Netflix guesses your next watch. How 50 companies already run on AI.
3.41
251
🤖 Ai In Business📋 Corporate Case Studies🧠 Applied Machine Learning
Artificial Intelligence in Practice Summary
Artificial Intelligence in Practice 86%
Robots patrol Walmart aisles. Netflix guesses your next watch. How 50 companies already run on AI.
by Bernard Marr 2019
3.41
251 ratings
🤖 Ai In Business📋 Corporate Case Studies🧠 Applied Machine Learning
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 86%
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
More Than Words
by John Warner • 2025
AI can mimic writing; only humans can actually write. The difference is the struggle to think.
4.05
525
💻 Technology And Writing✍️ Composition Theory🤖 Ai Criticism
More Than Words Summary
More Than Words 86%
AI can mimic writing; only humans can actually write. The difference is the struggle to think.
by John Warner 2025
4.05
525 ratings
💻 Technology And Writing✍️ Composition Theory🤖 Ai Criticism
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 86%
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
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 86%
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
Nicely Said
by Nicole Fenton • 2014
Your website has a voice. The rules for making it helpful, clear, and worth reading.
4.11
554
🖥️ Web Writing📋 Content Strategy🖱️ Ux Writing
Nicely Said Summary
Nicely Said 86%
Your website has a voice. The rules for making it helpful, clear, and worth reading.
by Nicole Fenton 2014
4.11
554 ratings
🖥️ Web Writing📋 Content Strategy🖱️ Ux Writing
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
ChatGPT for Beginners
by Eric Sarrion • 2023
How to use ChatGPT for emails, translations, and creative work, no AI experience needed.
2.20
5
🤖 AI Assistants✍️ Prompt Design⚡ AI Productivity
ChatGPT for Beginners Summary
ChatGPT for Beginners 86%
How to use ChatGPT for emails, translations, and creative work, no AI experience needed.
by Eric Sarrion 2023
2.20
5 ratings
🤖 AI Assistants✍️ Prompt Design⚡ AI Productivity
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 86%
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
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 86%
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
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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