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SoBrief
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Data Science for Business
by Foster Provost • 2013
Why overfitting sinks most data projects, and the conceptual tools that stop it.
4.13
3k+
Data Science for Business Summary
Data Science for Business 89%
Why overfitting sinks most data projects, and the conceptual tools that stop it.
by Foster Provost 2013
4.13
3k+ ratings
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
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
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
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
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+
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
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
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
Python Data Science Handbook
by Jake VanderPlas • 2016
Four libraries, one workflow: the Python path from raw data to validated predictions.
4.29
676
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
Low-Code AI
by Gwendolyn Stripling • 2023
Skip Python. Train regression models, engineer features, and explain predictions, all in SQL.
4.33
6
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
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
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
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 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 Simplified
by Andrew Wolf • 2022
Supervised learning, gently: pipeline, optimization, and the real reasons your model overfits.
4.87
193
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
Algorithms of the Intelligent Web
by Haralambos Marmanis • 2009
Search, recommend, cluster, classify: the algorithms that make web applications intelligent.
3.62
130
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
AI for Data Science
by Zacharias Voulgaris • 2018
The real AI toolkit goes beyond deep learning: optimization, fuzzy logic, ensembles.
4.55
20
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
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
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
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
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
The Elements of Statistical Learning
by Trevor Hastie • 2001
The unified mathematical engine under linear regression, trees, and neural nets.
4.43
2k+
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
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 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
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
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
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 Summary
Machine Learning 87%
From training models with labeled data to finding hidden patterns: the algorithms behind modern AI.
by Dr Ruchi Doshi 2021
5.00
1 ratings
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
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
Python for Geeks
by Muhammad Asif • 2021
Machine learning from notebook to production: Python libraries, data prep, and deployment paths.
4.50
8
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
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 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
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 Statistics for Data Scientists Summary
Practical Statistics for Data Scientists 87%
The statistical methods data scientists use daily, from boxplots to bootstrap, minus the proofs.
by Peter Bruce 2017
4.02
545 ratings
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
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
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
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
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
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
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
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
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+
Designing Machine Learning Systems Summary
Designing Machine Learning Systems 87%
Accuracy is not enough. An iterative playbook for machine learning systems that survive production.
by Chip Huyen 2022
4.45
1k+ ratings
Software Requirements
by Karl Wiegers • 1999
Nearly half of all software defects trace back to bad requirements. The fix starts here.
4.14
859
Software Requirements Summary
Software Requirements 87%
Nearly half of all software defects trace back to bad requirements. The fix starts here.
by Karl Wiegers 1999
4.14
859 ratings
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 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
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
Confident Data Skills Summary
Confident Data Skills 86%
From messy data to clean insights to persuasive presentations: the process that lands the promotion.
by Kirill Eremenko 2018
4.12
211 ratings
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
Everyday Chaos Summary
Everyday Chaos 86%
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
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+
Mastering Regular Expressions Summary
Mastering Regular Expressions 86%
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
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
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
Data Science from Scratch
by Joel Grus • 2015
Real understanding comes from building algorithms yourself, not calling libraries others wrote.
3.90
1k+
Data Science from Scratch Summary
Data Science from Scratch 86%
Real understanding comes from building algorithms yourself, not calling libraries others wrote.
by Joel Grus 2015
3.90
1k+ ratings
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
AI and Machine Learning for On-Device Development Summary
AI and Machine Learning for On-Device Development 86%
Privacy-respecting on-device AI: face detection, text analysis, custom models. No cloud, no PhD.
by Laurence Moroney 2021
4.17
6 ratings
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
Python for Data Analysis Summary
Python for Data Analysis 86%
Python data analysis, taught through questions: NumPy, Pandas, and the bridge to machine learning.
by Oscar Scratch 2019
3.50
2 ratings
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
Learning Python Data Visualization Summary
Learning Python Data Visualization 86%
Turn spreadsheets and web data into SVG charts with Python, no design background required.
by Chad Adams 2014
3.00
5 ratings
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
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
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
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
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+
The Master Algorithm Summary
The Master Algorithm 86%
Machine learning's rival schools share a hidden core. Finding it could unlock general intelligence.
by Pedro Domingos 2015
3.73
6k+ ratings
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
Neural Network for Beginners Summary
Neural Network for Beginners 86%
Stop treating neural networks as magic. Build them from scratch in Python, line by line.
by Sebastian Klaas 2021
5.00
1 ratings
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+
Big Data Summary
Big Data 86%
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
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 with Python Summary
Deep Learning with Python 86%
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 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 Design Patterns Summary
Deep Learning Design Patterns 86%
Data shift crushed your model? Simple design patterns push accuracy from 10% to 98%.
by Andrew Ferlitsch 2021
4.67
3 ratings
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
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
Python Scripting for ArcGIS Pro
by Paul Zandbergen • 2020
Automate ArcGIS Pro: convert a thousand files, rebuild maps, crunch rasters with Python you write.
4.13
23
Python Scripting for ArcGIS Pro Summary
Python Scripting for ArcGIS Pro 86%
Automate ArcGIS Pro: convert a thousand files, rebuild maps, crunch rasters with Python you write.
by Paul Zandbergen 2020
4.13
23 ratings
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
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
Learning OpenCV
by Gary Bradski • 2008
From smoothing to machine learning: the complete OpenCV toolkit for building computer vision apps.
4.01
171
Learning OpenCV Summary
Learning OpenCV 86%
From smoothing to machine learning: the complete OpenCV toolkit for building computer vision apps.
by Gary Bradski 2008
4.01
171 ratings
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 with Transformers Summary
Natural Language Processing with Transformers 86%
Build NLP applications with the open-source stack that turned transformer research practical.
by Lewis Tunstall 2022
4.39
211 ratings
Introduction to Computation and Programming Using Python
by John V. Guttag • 2013
A computer calculates and remembers; everything beyond that is what you build with code.
4.22
500
Introduction to Computation and Programming Using Python Summary
Introduction to Computation and Programming Using Python 86%
A computer calculates and remembers; everything beyond that is what you build with code.
by John V. Guttag 2013
4.22
500 ratings
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