🔄 Iterative Analysis

Methodologies for deepening understanding through repeated cycles of examination and refinement, where each pass through the data reveals new patterns and sharper insights.

Design Thinking Research

by Larry Leifer • 2013

What if your programming environment saved every change, so you could explore ideas without risk?

4.00

💻 Software Design 🗂️ Version Control 🔄 Iterative Development ✅ Code Quality Automation 🧠 Cognitive Load Reduction

Design Thinking Research 88%

What if your programming environment saved every change, so you could explore ideas without risk?

by Larry Leifer 2013

4.00

1 ratings

💻 Software Design 🗂️ Version Control 🔄 Iterative Development ✅ Code Quality Automation 🧠 Cognitive Load Reduction

Web Analytics 2.0

by Avinash Kaushik • 2009

Your web data is lying to you. The framework that turns page views into decisions.

4.13

2k+

🖥️ Digital Analytics 🎯 Performance Indicators 🧪 Online Experimentation 👥 Customer Intelligence 📈 Conversion Optimization

Web Analytics 2.0 88%

Your web data is lying to you. The framework that turns page views into decisions.

by Avinash Kaushik 2009

4.13

2k+ ratings

🖥️ Digital Analytics 🎯 Performance Indicators 🧪 Online Experimentation 👥 Customer Intelligence 📈 Conversion Optimization

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 🎓 Statistical Inference 🔄 Resampling Methods

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 🎓 Statistical Inference 🔄 Resampling Methods

Product Design for the Web

by Randy J. Hunt • 2013

Why shipping early and designing the invisible parts matters more than getting the pixels right.

3.76

278

📱 Product Design ✨ User Experience 🔄 Iterative Design 🧭 Usability 🏗️ Lean Methodology

Product Design for the Web 88%

Why shipping early and designing the invisible parts matters more than getting the pixels right.

by Randy J. Hunt 2013

3.76

278 ratings

📱 Product Design ✨ User Experience 🔄 Iterative Design 🧭 Usability 🏗️ Lean Methodology

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

📊 Data Science 🤖 Machine Learning 🔍 Exploratory Data Analysis ⚙️ Feature Engineering 📐 Model Evaluation

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 ⚙️ Feature Engineering 📐 Model Evaluation

Doing Rapid Qualitative Research

by Cecilia Vindrola-Padros • 2021

Fast enough for policy, deep enough for skeptics: qualitative methods that deliver both.

5.00

🧪 Qualitative Methods ⚡ Rapid Evaluation 📊 Program Evaluation 👥 Team-Based Research 🌍 Fieldwork Methods

Doing Rapid Qualitative Research Summary

Doing Rapid Qualitative Research 88%

Fast enough for policy, deep enough for skeptics: qualitative methods that deliver both.

by Cecilia Vindrola-Padros 2021

5.00

1 ratings

🧪 Qualitative Methods ⚡ Rapid Evaluation 📊 Program Evaluation 👥 Team-Based Research 🌍 Fieldwork Methods

Lean Software Development

by Mary Poppendieck • 2003

The lean manufacturing toolkit, adapted for software teams: cut waste, ship faster, decide later.

4.19

1k+

🏭 Lean Methodology 🔄 Agile Methods 🚀 Continuous Delivery 🤝 Team Autonomy 🧩 Systems Thinking

Lean Software Development 88%

The lean manufacturing toolkit, adapted for software teams: cut waste, ship faster, decide later.

by Mary Poppendieck 2003

4.19

1k+ ratings

🏭 Lean Methodology 🔄 Agile Methods 🚀 Continuous Delivery 🤝 Team Autonomy 🧩 Systems Thinking

Modern Software Engineering

by David Farley • 2021

Software is not a craft; it's a science. The discipline that turns teams into learning machines.

4.16

1k+

🔬 Scientific Engineering 🔄 Continuous Delivery 🔁 Feedback Loops 🧱 Modularity 🧪 Testability

Modern Software Engineering 88%

Software is not a craft; it's a science. The discipline that turns teams into learning machines.

by David Farley 2021

4.16

1k+ ratings

🔬 Scientific Engineering 🔄 Continuous Delivery 🔁 Feedback Loops 🧱 Modularity 🧪 Testability

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 📊 Statistical Modeling 🎲 Hypothesis Testing

Think Stats 88%

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 📊 Statistical Modeling 🎲 Hypothesis Testing

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 🔄 Resampling Methods 📈 Regression Modeling

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 🔄 Resampling Methods 📈 Regression Modeling

Debugging

by David J. Agans • 2002

Learn to debug like a detective: reproduce the crime, divide the scene, and never guess.

4.26

509

🐛 Debugging 🎯 Root Cause Analysis ⚙️ Engineering Mindset 🔧 Pragmatic Programming 🧪 Scientific Method

Debugging 88%

Learn to debug like a detective: reproduce the crime, divide the scene, and never guess.

by David J. Agans 2002

4.26

509 ratings

🐛 Debugging 🎯 Root Cause Analysis ⚙️ Engineering Mindset 🔧 Pragmatic Programming 🧪 Scientific Method

Behind Every Good Decision

by Piyanka Jain • 2014

Analytics problems rarely need data scientists. A five-step framework anyone with Excel can use.

3.60

144

📊 Business Analytics 📈 Data-Driven Decisions 🧩 Analytics Frameworks 📖 Data Literacy 🔧 Everyday Analytics

Behind Every Good Decision 88%

Analytics problems rarely need data scientists. A five-step framework anyone with Excel can use.

by Piyanka Jain 2014

3.60

144 ratings

📊 Business Analytics 📈 Data-Driven Decisions 🧩 Analytics Frameworks 📖 Data Literacy 🔧 Everyday Analytics

PYTHON FOR DATA ANALYSIS

by Ryshith Doyle • 2019

The systematic NumPy and Pandas walkthrough: import, clean, combine, and analyze data in Python.

3.67

🐍 Python Programming 📊 Data Analysis 🧹 Data Wrangling 🧱 Data Structures 🔢 Numerical Computing

PYTHON FOR DATA ANALYSIS 87%

The systematic NumPy and Pandas walkthrough: import, clean, combine, and analyze data in Python.

by Ryshith Doyle 2019

3.67

6 ratings

🐍 Python Programming 📊 Data Analysis 🧹 Data Wrangling 🧱 Data Structures 🔢 Numerical Computing

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 Overload 🔍 Everyday Patterns

Information Is Beautiful 87%

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 🌊 Information Overload 🔍 Everyday Patterns

How to Speak Machine

by John Maeda • 2019

Loops, scale, and unfinished products: what computers know that designers must learn.

3.69

521

🖥️ Computational Thinking 📱 Digital Design 🔄 Iterative Development ⚖️ Algorithmic Bias 📊 Data-Driven Design

How to Speak Machine 87%

Loops, scale, and unfinished products: what computers know that designers must learn.

by John Maeda 2019

3.69

521 ratings

🖥️ Computational Thinking 📱 Digital Design 🔄 Iterative Development ⚖️ Algorithmic Bias 📊 Data-Driven Design

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 🤝 Ensemble Learning ⚖️ Regularization Methods

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 🤝 Ensemble Learning ⚖️ Regularization Methods

Software Requirements

by Karl Wiegers • 1999

Nearly half of all software defects trace back to bad requirements. The fix starts here.

4.14

859

🏗️ Requirements Engineering 👤 User-Centered Design ✅ Software Quality 📋 Project Management 📊 Business Analysis

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

🏗️ Requirements Engineering 👤 User-Centered Design ✅ Software Quality 📋 Project Management 📊 Business Analysis

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 💻 Digital Strategy 🔓 Open Platforms

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 💻 Digital Strategy 🔓 Open Platforms

The Art of Doing Science and Engineering

by Richard W. Hamming • 1996

What separates great scientists from good ones: they pick better problems.

4.18

2k+

🧠 Scientific Thinking ⚙️ Engineering Practice 💻 Computational Thinking 🔬 Research Methods 🔗 Interdisciplinary

The Art of Doing Science and Engineering Summary

The Art of Doing Science and Engineering 87%

What separates great scientists from good ones: they pick better problems.

by Richard W. Hamming 1996

4.18

2k+ ratings

🧠 Scientific Thinking ⚙️ Engineering Practice 💻 Computational Thinking 🔬 Research Methods 🔗 Interdisciplinary

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 📈 Model Evaluation 🧹 Data Preparation

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 📈 Model Evaluation 🧹 Data Preparation

Python for Excel

by Felix Zumstein • 2021

Turn Excel into a Python engine: automate reports, scale past a million rows, and quit copy-pasting.

4.00

📊 Data Analysis 🤖 Spreadsheet Automation 🐼 Pandas Dataframes 📈 Time Series Analysis 📄 Reproducible Reporting

Python for Excel 87%

Turn Excel into a Python engine: automate reports, scale past a million rows, and quit copy-pasting.

by Felix Zumstein 2021

4.00

41 ratings

📊 Data Analysis 🤖 Spreadsheet Automation 🐼 Pandas Dataframes 📈 Time Series Analysis 📄 Reproducible Reporting

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 🔮 Future Of Work 📊 Data Governance

Superagency 87%

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 🔮 Future Of Work 📊 Data Governance

Introduction to Real Analysis

by Robert G. Bartle • 1982

A rigorous foundation in real numbers and limits: the proofs that make calculus unshakeable.

4.00

311

🧮 Real Analysis 📐 Rigorous Calculus 📝 Mathematical Proofs 🔢 Sequences And Series 🌀 Point-Set Topology

Introduction to Real Analysis 87%

A rigorous foundation in real numbers and limits: the proofs that make calculus unshakeable.

by Robert G. Bartle 1982

4.00

311 ratings

🧮 Real Analysis 📐 Rigorous Calculus 📝 Mathematical Proofs 🔢 Sequences And Series 🌀 Point-Set Topology

Practical SQL

by Anthony DeBarros • 2022

Write real SQL: load data, join tables, run statistics, map locations, and query JSON in PostgreSQL.

4.26

239

💾 Sql 📊 Data Analysis 🗃️ Relational Databases 📖 Data Storytelling 🛠️ Learn By Doing

Practical SQL 87%

Write real SQL: load data, join tables, run statistics, map locations, and query JSON in PostgreSQL.

by Anthony DeBarros 2022

4.26

239 ratings

💾 Sql 📊 Data Analysis 🗃️ Relational Databases 📖 Data Storytelling 🛠️ Learn By Doing

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 🌐 Quantified World 🔗 Correlation Analysis

Big Data 87%

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 🌐 Quantified World 🔗 Correlation 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 🔧 Feature Engineering 🧹 Data Preparation

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 🔧 Feature Engineering 🧹 Data Preparation

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 🧩 Unsupervised Learning ⚖️ Data Ethics

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 🧩 Unsupervised Learning ⚖️ Data Ethics

The Model Thinker

by Scott E. Page • 2018

Big data without many models is just noise. The case for thinking through multiple frameworks.

3.92

955

🧠 Mental Models 🔄 Systems Thinking 🌀 Complexity Science 📊 Quantitative Reasoning 🕸️ Network Theory

The Model Thinker 87%

Big data without many models is just noise. The case for thinking through multiple frameworks.

by Scott E. Page 2018

3.92

955 ratings

🧠 Mental Models 🔄 Systems Thinking 🌀 Complexity Science 📊 Quantitative Reasoning 🕸️ Network Theory

Rational Choice and Security Studies

by Michael E. Brown • 2000

Two visions of political science: one builds mathematical temples, the other wants to stop war.

3.78

🔒 Security Studies 🧮 Rational Choice ⚔️ Methodology Wars 🔬 Philosophy Of Science 📐 Formal Modeling

Rational Choice and Security Studies Summary

Rational Choice and Security Studies 87%

Two visions of political science: one builds mathematical temples, the other wants to stop war.

by Michael E. Brown 2000

3.78

9 ratings

🔒 Security Studies 🧮 Rational Choice ⚔️ Methodology Wars 🔬 Philosophy Of Science 📐 Formal Modeling

Python Data Science

by Christopher Wilkinson • 2019

Python taught for data science: syntax, data structures, and the libraries that unlock the field.

2.50

🐍 Python Programming 📊 Data Science 📐 Programming Fundamentals 🔧 Data Analysis Tools 🌐 Python Ecosystem

Python Data Science 87%

Python taught for data science: syntax, data structures, and the libraries that unlock the field.

by Christopher Wilkinson 2019

2.50

2 ratings

🐍 Python Programming 📊 Data Science 📐 Programming Fundamentals 🔧 Data Analysis Tools 🌐 Python Ecosystem

Data Analytics Made Accessible

by Anil Maheshwari • 2014

Every analytics technique a manager needs, from decision trees to big data, mapped and demystified.

3.76

323

🧱 Data Analytics 📊 Business Intelligence ⛏️ Data Mining 📈 Data Visualization 🔮 Predictive Analytics

Data Analytics Made Accessible 87%

Every analytics technique a manager needs, from decision trees to big data, mapped and demystified.

by Anil Maheshwari 2014

3.76

323 ratings

🧱 Data Analytics 📊 Business Intelligence ⛏️ Data Mining 📈 Data Visualization 🔮 Predictive Analytics

Python for Data Analysis

by Oscar Scratch • 2019

Python data analysis, taught through questions: NumPy, Pandas, and the bridge to machine learning.

3.50

🧮 Scientific Computing 🔄 Data Manipulation 📊 Data Visualization 🐍 Introductory Programming 📈 Beginner Data Science

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 🐍 Introductory Programming 📈 Beginner Data Science

Paper Prototyping

by Carolyn Snyder • 2003

Paper screens, a colleague at the controls: find the fatal flaws while fixing them is free.

3.78

207

🎨 User Experience Design 🧪 Usability Testing ✂️ Rapid Prototyping 🔄 Iterative Design 🔍 User Research

Paper Prototyping 87%

Paper screens, a colleague at the controls: find the fatal flaws while fixing them is free.

by Carolyn Snyder 2003

3.78

207 ratings

🎨 User Experience Design 🧪 Usability Testing ✂️ Rapid Prototyping 🔄 Iterative Design 🔍 User Research

Low-Code AI

by Gwendolyn Stripling • 2023

Skip Python. Train regression models, engineer features, and explain predictions, all in SQL.

4.33

🛠️ Practical Ml 📊 Data Exploration 🔧 Feature Engineering 🔍 Model Interpretability 🧩 Low-Code Platforms

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 🔍 Model Interpretability 🧩 Low-Code Platforms

Agile Project Management with Scrum

by Ken Schwaber • 2004

Stop fighting uncertainty. Ship working software every 30 days with a framework built for change.

3.71

2k+

🏃 Agile Project Management 🔄 Iterative Development 📈 Continuous Improvement ⏱️ Timeboxing 🤝 Self-Organizing Teams

Agile Project Management with Scrum Summary

Agile Project Management with Scrum 87%

Stop fighting uncertainty. Ship working software every 30 days with a framework built for change.

by Ken Schwaber 2004

3.71

2k+ ratings

🏃 Agile Project Management 🔄 Iterative Development 📈 Continuous Improvement ⏱️ Timeboxing 🤝 Self-Organizing Teams

Scrum for Dummies

by Mark C. Layton • 2014

Projects go off the rails one task at a time. Scrum catches them every 24 hours.

3.76

124

🏃 Agile Methods 📋 Project Management 🔄 Iterative Development 📈 Continuous Improvement 🤝 Team Collaboration

Scrum for Dummies 87%

Projects go off the rails one task at a time. Scrum catches them every 24 hours.

by Mark C. Layton 2014

3.76

124 ratings

🏃 Agile Methods 📋 Project Management 🔄 Iterative Development 📈 Continuous Improvement 🤝 Team Collaboration

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

📈 Time Series Analysis 🔧 Feature Engineering 🧹 Data Preparation ⚙️ Machine Learning Pipelines 📊 Statistical Learning

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 ⚙️ Machine Learning Pipelines 📊 Statistical Learning

Game Design Workshop

by Tracy Fullerton • 2008

The prototyping-first method that catches design disasters before you write a single line of code.

4.11

513

🎮 Game Design 📐 Rapid Prototyping 🔄 Iterative Design ⚙️ Game Mechanics 🌱 Emergent Gameplay

Game Design Workshop 87%

The prototyping-first method that catches design disasters before you write a single line of code.

by Tracy Fullerton 2008

4.11

513 ratings

🎮 Game Design 📐 Rapid Prototyping 🔄 Iterative Design ⚙️ Game Mechanics 🌱 Emergent Gameplay

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 🎢 Emotional Arcs 🎯 Character Agency

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 🎢 Emotional Arcs 🎯 Character Agency

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 📊 Data-Driven Decisions 📘 Technical Primers

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 📊 Data-Driven Decisions 📘 Technical Primers

Research Methodology

by C.R. Kothari • 1985

The gap between a research question and a publishable finding, bridged step by step.

3.88

306

🧪 Research Methodology 📊 Quantitative Methods 📐 Research Design 🔬 Hypothesis Testing 📈 Multivariate Analysis

Research Methodology 87%

The gap between a research question and a publishable finding, bridged step by step.

by C.R. Kothari 1985

3.88

306 ratings

🧪 Research Methodology 📊 Quantitative Methods 📐 Research Design 🔬 Hypothesis Testing 📈 Multivariate Analysis

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

🧑‍💻 Introductory Programming 🧠 Computational Thinking 🐍 Python For Beginners 📐 Algorithm Design 🗃️ Data Structures

Introduction to Computation and Programming Using Python Summary

Introduction to Computation and Programming Using Python 87%

A computer calculates and remembers; everything beyond that is what you build with code.

by John V. Guttag 2013

4.22

500 ratings

🧑‍💻 Introductory Programming 🧠 Computational Thinking 🐍 Python For Beginners 📐 Algorithm Design 🗃️ Data Structures

Business Analyst's Mentor Book

by Emrah Yayici • 2013

The 80/20 business-IT formula, plus requirements, agile, and UX techniques to save your projects.

3.67

187

📊 Business Analysis 📋 Requirements Management 🔄 Agile Methodology 🎨 User-Centered Design 🔍 Usability Testing

Business Analyst's Mentor Book 87%

The 80/20 business-IT formula, plus requirements, agile, and UX techniques to save your projects.

by Emrah Yayici 2013

3.67

187 ratings

📊 Business Analysis 📋 Requirements Management 🔄 Agile Methodology 🎨 User-Centered Design 🔍 Usability Testing

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 🧹 Data Preprocessing ⚙️ Feature Engineering

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 🧹 Data Preprocessing ⚙️ Feature Engineering

Why Greatness Cannot Be Planned

by Kenneth O. Stanley • 2015

Ambitious objectives blind you to the very discoveries that make them obsolete.

3.98

1k+

💡 Innovation Studies 🚫 Goal Skepticism ✨ Serendipity And Discovery 🧬 Evolutionary Thinking 🎨 Creative Process

Why Greatness Cannot Be Planned 87%

Ambitious objectives blind you to the very discoveries that make them obsolete.

by Kenneth O. Stanley 2015

3.98

1k+ ratings

💡 Innovation Studies 🚫 Goal Skepticism ✨ Serendipity And Discovery 🧬 Evolutionary Thinking 🎨 Creative Process

User Story Mapping

by Jeff Patton • 2012

A $125M crash taught us written specs fail. This visual technique catches the misunderstanding.

4.19

4k+

📝 User Stories 🧠 Shared Understanding 🔍 Product Discovery ✏️ Visual Thinking 🔄 Iterative Delivery

User Story Mapping 87%

A $125M crash taught us written specs fail. This visual technique catches the misunderstanding.

by Jeff Patton 2012

4.19

4k+ ratings

📝 User Stories 🧠 Shared Understanding 🔍 Product Discovery ✏️ Visual Thinking 🔄 Iterative Delivery

Little Bets

by Peter Sims • 2011

Big visions are overrated. Real innovators run dozens of small experiments instead.

3.77

4k+

🧪 Innovation Methods 🔄 Iterative Design 📉 Learning From Failure 🎨 Creative Process ⚙️ Lean Methodology

Little Bets 87%

Big visions are overrated. Real innovators run dozens of small experiments instead.

by Peter Sims 2011

3.77

4k+ ratings

🧪 Innovation Methods 🔄 Iterative Design 📉 Learning From Failure 🎨 Creative Process ⚙️ Lean Methodology

User Stories Applied

by Mike Cohn • 2004

Replace bloated specs with user stories, hours with story points, and hope with velocity.

3.89

3k+

🧱 Agile Methodology 💻 Software Development 📝 Requirements Gathering 📏 Project Estimation ✅ Acceptance Testing

User Stories Applied 87%

Replace bloated specs with user stories, hours with story points, and hope with velocity.

by Mike Cohn 2004

3.89

3k+ ratings

🧱 Agile Methodology 💻 Software Development 📝 Requirements Gathering 📏 Project Estimation ✅ Acceptance Testing

Keeping Up with the Quants

by Thomas H. Davenport • 2013

You hired the quants. Now learn the questions that turn their numbers into decisions.

3.57

585

🏢 Data-Driven Management 📊 Business Analytics 🧮 Quantitative Thinking 📖 Data Storytelling 📋 Evidence-Based Management

Keeping Up with the Quants 87%

You hired the quants. Now learn the questions that turn their numbers into decisions.

by Thomas H. Davenport 2013

3.57

585 ratings

🏢 Data-Driven Management 📊 Business Analytics 🧮 Quantitative Thinking 📖 Data Storytelling 📋 Evidence-Based Management

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 📋 Reproducible Ml 🤝 Ensemble Learning

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

⚙️ Machine Learning Engineering 🔧 Mlops 🔄 Iterative Design 📋 Reproducible Ml 🤝 Ensemble Learning

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