Vidas Secas

Sort of Recommender Systems

1. Collaborative filtering methods 
1. Memory-based methods
1. User-based collaborative filtering
2. Item-based collaborative filtering
2. Model-based methods
2. Content-based recommender methods 
3. Knowledge-based recommender systems
4. Hybrid systems

All of them are based on:

• Agent interactions – dynamic or time oriented
• Item attributes – static or features oriented
• Ratings matrices

Recommender Systems

Recommender systems are, after all, utilized by merchants to increase their profit. In order to achieve the broader business-centric goal of increasing revenue, the common operational and technical goals of recommender systems are as follows:

1. Relevance: The most obvious operational goal of a recommender system is to recommend items that are relevant to the user at hand. Users are more likely to consume items they find interesting. Although relevance is the primary operational goal of a recommender system, it is not sufficient in isolation. Therefore, we discuss several secondary goals below, which are not quite as important as relevance but are nevertheless important enough to have a significant impact.
2. Novelty: Recommender systems are truly helpful when the recommended item is something that the user has not seen in the past. For example, popular movies of a preferred genre would rarely be novel to the user. Repeated recommendation of popular items can also lead to reduction in sales diversity.
3. Serendipity: A related notion is that of serendipity [229], wherein the items recommended are somewhat unexpected, and therefore there is a modest element of lucky discovery, as opposed to obvious recommendations. Serendipity is different from novelty in that the recommendations are truly surprising to the user, rather than simply something they did not know about before. It may often be the case that a particular user may only be consuming items of a specific type, although a latent interest in items of other types may exist which the user might themselves find surprising. Unlike novelty, serendipitous methods focus on discovering such recommendations. For example, if a new Indian restaurant opens in a neighbourhood, then the recommendation of that restaurant to a user who normally eats Indian food is novel but not necessarily serendipitous. On the other hand, when the same user is recommended Ethiopian food, and it was unknown to the user that such food might appeal to her, then the recommendation is serendipitous. Serendipity has the beneficial side effect of increasing sales diversity or beginning a new trend of interest in the user. Increasing serendipity often has long-term and strategic benefits to the merchant because of the possibility of discovering entirely new areas of interest. On the other hand, algorithms that provide serendipitous recommendations often tend to recommend irrelevant items. In many cases, the longer term and strategic benefits of serendipitous methods outweigh these short-term disadvantages.
4. Increasing recommendation diversity: Recommender systems typically suggest a list of top-k items. When all these recommended items are very similar, it increases the risk that the user might not like any of these items. On the other hand, when the recommended list contains items of different types, there is a greater chance that the user might like at least one of these items. Diversity has the benefit of ensuring that the user does not get bored by repeated recommendation of similar items.

Loneliness

Process mining as the bridge between data science and process science

Process science is an umbrella term for the broader discipline that combines knowledge from information technology and knowledge from management sciences to improve and run operational processes

The ingredients contributing to data science

Data science

Data science is an interdisciplinary field aiming to turn data into real value. Data may be structured or unstructured, big or small, static or streaming. Value may be provided in the form of predictions, automated decisions, mod- els learned from data, or any type of data visualization delivering insights. Data science includes data extraction, data preparation, data exploration, data transformation, storage and retrieval, computing infrastructures, var- ious types of mining and learning, presentation of explanations and pre- dictions, and the exploitation of results taking into account ethical, social, legal, and business aspects.

The above definition implies that data science is broader than applied statistics and data mining. Data scientists assist organizations in turning data into value. A data scientist can answer a variety of data-driven questions. These can be grouped into the following four main categories:

• (Reporting) What happened?
• (Diagnosis) Why did it happen?
• (Prediction) What will happen?
• (Recommendation) What is the best that can happen?

An example of a customer journey illustrating the many (digital) touchpoints generating events that allow us to understand and serve customers better

Internet of Events

From Big Data to Smart Data, a closed loop

Universum - Urbi et Orbi

Emoções

Computer Science Spectre

Educação

Something's just not right

Hardware Description of Disk Devices

Simplified IR process pipeline

A Comparison of Databases and IR Systems

Computer Science Bibliography

1. Introduction to Algorithms - by Thomas H. Cormen 
2. Structure and Interpretation of Computer Programs - by Harold Abelson 
3. The C Programming Language - by Brian W. Kernighan 
4. The Pragmatic Programmer: From Journeyman to Master - by Andy Hunt
5. The Art of Computer Programming, Volumes 1-3 Boxed Set - by Donald Ervin Knuth 
6. Design Patterns: Elements of Reusable Object-Oriented Software - by Erich Gamma 
7. Introduction to the Theory of Computation - by Michael Sipser 
8. Code: The Hidden Language of Computer Hardware and Software - by Charles Petzold 
9. The Mythical Man-Month: Essays on Software Engineering - by Frederick P. Brooks Jr. 
10. Artificial Intelligence: A Modern Approach - by Stuart Russell 
11. Code Complete - by Steve McConnell 
12. The Protocols (TCP/IP Illustrated, Volume 1) - by W. Richard Stevens 
13. Algorithms - by Robert Sedgewick 
14. Advanced Programming in the UNIX Environment - by W. Richard Stevens 
15. A Discipline of Programming - by Edsger W. Dijkstra 
16. Introduction to Automata Theory, Languages, and Computation - by John E. Hopcroft 
17. Compilers: Principles, Techniques, and Tools - by Alfred V. Aho 
18. Learn You a Haskell for Great Good!: A Beginner's Guide - by Miran Lipovača 
19. The Society of Mind - by Marvin Minsky 
20. Concrete Mathematics: A Foundation for Computer Science - by Ronald L. Graham 
21. An Introduction to Functional Programming Through Lambda Calculus - by Greg Michaelson 
22. The STREAM TONE: The Future of Personal Computing? - by T. Gilling 
23. Fundamental Kotlin - by Miloš Vasić
24. The Algorithm Design Manual - by Steven S. Skiena 
25. Programming Pearls - by Jon L. Bentley 
26. The Elements of Computing Systems: Building a Modern Computer from First Principles - by Noam Nisan 
27. The Psychology of Computer Programming - by Gerald M. Weinberg
28. Applied Cryptography: Protocols, Algorithms, and Source Code in C - by Bruce Schneier 
29. Hacker's Delight - by Henry S. Warren Jr. 
30. Database System Concepts - by Abraham Silberschatz 
31. A First Course in Logic: An Introduction to Model Theory, Proof Theory, Computability, and Complexity - by Shawn Hedman 
32. Computer Systems: A Programmer's Perspective - by Randal E. Bryant 
33. Basic Proof Theory - by Anne S. Troelstra 
34. Structured Computer Organization - by Andrew S. Tanenbaum 
35. Quality Software Management: Systems Thinking - by Gerald M. Weinberg 
36. Computability and Logic - by George S. Boolos 
37. Waltzing with Bears: Managing Risk on Software Projects - by Tom DeMarco 
38. An Introduction to Database Systems - by C.J. Date 
39. Chaos: Making a New Science - by James Gleick 
40. What Is Life? with Mind and Matter and Autobiographical Sketches - by Erwin Schrödinger 
41. The Annotated Turing: A Guided Tour Through Alan Turing's Historic Paper on Computability and the Turing Machine - by Charles Petzold 
42. Feynman Lectures On Computation - by Richard Feynman 
43. Computational Complexity - by Christos H. Papadimitriou 
44. The Fractal Geometry of Nature - by Benoît B. Mandelbrot 
45. Exploring Requirements: Quality Before Design - by Donald C. Gause 
46. The It Handbook for Business: Managing Information Technology Support Costs - by William C. Couie 
47. Six Degrees: The Science of a Connected Age - by Duncan J. Watts 
48. Computability and Unsolvability - by Martin D. Davis 
49. Communication Networks: Fundamental Concepts and Key Architectures - by Alberto Leon-Garcia 
50. Computability Theory - by S. Barry Cooper 
51. Journey through Genius: The Great Theorems of Mathematics - by William Dunham 
52. The Quark and the Jaguar: Adventures in the Simple and the Complex - by Murray Gell-Mann 
53. Sync: The Emerging Science of Spontaneous Order - by Steven H. Strogatz 
54. How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life - by Albert-László Barabási 
55. Engines of Creation: The Coming Era of Nanotechnology - by K. Eric Drexler 
56. Refactoring: Improving the Design of Existing Code - by Martin Fowler 
57. Slack: Getting Past Burnout, Busywork, and the Myth of Total Efficiency - by Tom DeMarco 
58. Elements of the Theory of Computation - by Harry R. Lewis 
59. Lambda-Calculus and Combinators: An Introduction - by J. Roger Hindley 
60. Lambda-Calculus, Combinators and Functional Programming - by György E. Révész 
61. Design and Validation of Computer Protocols - by Gerard J. Holzmann 
62. File Structures: An Object-Oriented Approach with C++ - by Michael J. Folk 
63. Debugging: The 9 Indispensable Rules for Finding Even the Most Elusive Software and Hardware Problems - by David J. Agans
64. The Meme Machine - by Susan Blackmore 
65. Does God Play Dice?: The New Mathematics of Chaos - by Ian Stewart 
66. The Strangest Man: The Hidden Life of Paul Dirac, Mystic of the Atom - by Graham Farmelo 
67. The Hidden Connections: A Science for Sustainable Living - by Fritjof Capra 
68. Purely Functional Data Structures - by Chris Okasaki 
69. The Calculus of Computation: Decision Procedures with Applications to Verification - by Aaron R. Bradley 
70. Cracking the Coding Interview: 150 Programming Questions and Solutions - by Gayle Laakmann McDowell 
71. Modern Operating Systems - by Andrew S. Tanenbaum 
72. Algorithm Design - by Jon Kleinberg 
73. Source Code Optimization Techniques For Data Flow Dominated Embedded Software - by Heiko Falk 
74. Advanced Compiler Design and Implementation - by Steven S. Muchnick 
75. A Practical Introduction to Computer Architecture - by Daniel Page 
76. Patterns of Enterprise Application Architecture - by Martin Fowler 
77. The Science of Liberty: Democracy, Reason and the Laws of Nature - by Timothy Ferris 
78. Reinventing Discovery: The New Era of Networked Science - by Michael Nielsen
79. On Growth and Form - by D'Arcy Wentworth Thompson 
80. Cycles of Time: An Extraordinary New View of the Universe - by Roger Penrose 
81. Chances Are . . .: Adventures in Probability - by Michael Kaplan 
82. Angels and Ages: A Short Book About Darwin, Lincoln, and Modern Life - by Adam Gopnik 
83. Total Recall: How the E-Memory Revolution Will Change Everything - by C. Gordon Bell 
84. Annoying: The Science of What Bugs Us - by Joe Palca 
85. Collider: The Search for the World's Smallest Particles - by Paul Halpern
86. Denialism: How Irrational Thinking Hinders Scientific Progress, Harms the Planet, and Threatens Our Lives - by Michael Specter 
87. Six Impossible Things Before Breakfast: The Evolutionary Origins of Belief 
88. by Lewis Wolpert 
89. The Pleasure Instinct: Why We Crave Adventure, Chocolate, Pheromones, and Music 
90. by Gene Wallenstein 
91. Shadows of the Mind: A Search for the Missing Science of Consciousness - by Roger Penrose 
92. The Age of Entanglement: When Quantum Physics Was Reborn - by Louisa Gilder 
93. The Clockwork Universe: Isaac Newton, the Royal Society, and the Birth of the Modern World - by Edward Dolnick 
94. Quantum Man: Richard Feynman's Life in Science - by Lawrence M. Krauss 
95. The Day We Found the Universe - by Marcia Bartusiak 
96. A New Kind of Science - by Stephen Wolfram 
97. Letters to a Young Mathematician - by Ian Stewart 
98. A History of π - by Petr Beckmann 
99. Out of Control: The New Biology of Machines, Social Systems, and the Economic World - by Kevin Kelly 
100. The User Illusion: Cutting Consciousness Down to Size - by Tor Nørretranders 
101. Programming the Universe: A Quantum Computer Scientist Takes on the Cosmos - by Seth Lloyd 
102. Biology as Ideology: The Doctrine of DNA - by Richard C. Lewontin 
103. The End of Time: The Next Revolution in Our Understanding of the Universe - by Julian Barbour 
104. A World Without Time: The Forgotten Legacy of Gödel And Einstein - by Palle Yourgrau 
105. Dreams of a Final Theory: The Scientist's Search for the Ultimate Laws of Nature - by Steven Weinberg 
106. The Trouble with Physics: The Rise of String Theory, the Fall of a Science and What Comes Next - by Lee Smolin 
107. Your Brain at Work: Strategies for Overcoming Distraction, Regaining Focus, and Working Smarter All Day Long - by David Rock 
108. Unequal Protection: The Rise of Corporate Dominance and the Theft of Human Rights - by Thom Hartmann 
109. Poor Charlie's Almanack: The Wit and Wisdom of Charles T. Munger - by Charles T. Munger 
110. Eight Little Piggies: Reflections in Natural History - by Stephen Jay Gould 
111. The Smart Swarm: How Understanding Flocks, Schools, and Colonies Can Make Us Better at Communicating, Decision Making, and Getting Things Done - by Peter Miller 
112. Emergence: The Connected Lives of Ants, Brains, Cities, and Software - by Steven Johnson 
113. The Body Has a Mind of Its Own: How Body Maps in Your Brain Help You Do (Almost) Everything Better - by Sandra Blakeslee 
114. The Age of Empathy: Nature's Lessons for a Kinder Society - by Frans de Waal 
115. Wholeness and the Implicate Order - by David Bohm 
116. The Structure of Evolutionary Theory - by Stephen Jay Gould 
117. The Evolution of Cooperation - by Robert Axelrod 
118. Philosophy in the Flesh: The Embodied Mind and its Challenge to Western Thought - by George Lakoff 
119. Quantum: Einstein, Bohr and the Great Debate About the Nature of Reality - by Manjit Kumar 
120. The Theory of Almost Everything: The Standard Model, the Unsung Triumph of Modern Physics - by Robert Oerter 
121. Seeking Wisdom: From Darwin To Munger - by Peter Bevelin 
122. The Master and His Emissary: The Divided Brain and the Making of the Western World - by Iain McGilchrist 
123. Complexity, adaptive leadership, phase transitions, and new emergent order: A case study of the Northwest Texas Conference of the United Methodist Church. - by Bryan D. Sims 
124. Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation - by Michael J. North 
125. The Emperor's Nightingale: How the Emerging Dynamics of Corporate Complexity Will Restore Life in the New Millennium - by Robert A.G. Monks
126. Machines, Languages, And Complexity: 5th International Meeting Of Young Computer Scientists, Smolenice, Czechoslovakia, November 14 18, 1988: Selected Contributions - by Jürgen Dassow
127. Regional Pathways to Complexity: Settlement and Land-Use Dynamics in Early Italy from the Bronze Age to the Republican Period - by Peter Attema 
128. Nonlinear Dynamics of Chaotic and Stochastic Systems: Tutorial and Modern Developments. Springer Complexity, Springer Series in Synergetics. - by Vadim S. Anishchenko 
129. Complexity Theory and the Management of Networks: Proceedings of the Workshop on Organisational Networks as Distributed Systems of Knowledge - by Pierpaolo Andriani
130. The New Economy and Macroeconomic Stability: A Neo-Modern Perspective Drawing on the Complexity Approach and Keynesian Economics - by Dario Togati 
131. Applications of Automata Theory and Algebra: Via the Mathematical Theory of Complexity to Biology, Physics, Psychology, Philosophy, and Games - by John L. Rhodes 
132. The Effective Organization: Practical Application of Complexity Theory and Organizational Design to Maximize Performance in the Face of Emerging Events - by Dennis A. Tafoya 
133. AI Approaches to the Complexity of Legal Systems: Complex Systems, the Semantic Web, Ontologies, Argumentation, and Dialogue - by Pompeu Casanovas 
134. Resource Efficiency Complexity and the Commons: The Paracommons and Paradoxes of Natural Resource Losses, Wastes and Wastages - by Bruce Lankford 
135. On the (Im)Possibility of Business Ethics: Critical Complexity, Deconstruction, and Implications for Understanding the Ethics of Business - by Minka Woermann  

Common Exponential Distributions and their Sufficient Statistics

Traditional Programming x Machine Learning

3D Euclidean Distance

Scatter plots illustrating correlations from -1 to1

Amostragem

General Types of Sampling

Full Table Scan x Index Scan

Steps to better code

https://dev.to/isaacandsuch/steps-to-better-code

Hemispheres

Map of Computer Science

Mito platônico descrito na República

A idéia é a seguinte: é descrita uma situação na qual  escravos são criados desde o seu nascimento acorrentados em uma caverna de tal modo que jamais possam virar-se para trás e a única coisa que vêem consiste em sombras projetadas na parede em sua frente, relativas à luz de uma fogueira localizada atrás dos mesmos. Para estes escravos, portanto, o mundo é composto apenas por estas projeções e nada mais.

Um belo dia, um dos escravos se solta das algemas e, tateando as paredes da caverna, acaba por subir à superfície. Ao se deparar com o mundo exterior, primeiro é ofuscado pela luz do Sol. Em seguida, conforme vai se acostumando à luz, começa a observar objetos que jamais havia sonhado: árvores, grama, animais, casas, para seu espanto outros homens e, finalmente, o céu. Óbviamente, nosso escravo fica maravilhado. E, de tão maravilhado que fica, decide voltar à caverna para contar a seus companheiros a novidade. Ao fazê-lo, primeiro é tido como louco para, em seguida, ser assassinado pelos mesmos.

The 48 Laws of Power (Animated)

Computational intelligence

Computational intelligence as the computational models and tools of intelligence capable of inputting raw numerical sensory data directly, processing them by exploiting the representational parallelism and pipelining of the problem, generating reliable & timely responses and withstanding high fault tolerance.

Computational Intelligence

A system is computationally intelligent when it: deals with only numerical (low level) data, has pattern recognition components, does not use knowledge in the AI sense: and additionally when it (begins to) exhibit i) computational adaptivity, ii) computational fault tolerance, Hi) speed approaching human-like turnaround and iv) error rates that approximate human performance.

• PR= Probabilistic reasoning
• BN= Belief networks
• FL= Fuzzy logic
• NN= Neural nets
• GA= Genetic algorithms
• EP= Evolutionary programming
• AL= Artificial life

Systematic literature review process.

A comparison of the scientific method (on the left) with the role of experimentation in system design (right)

The Scientific Method

Inteligência Artificial sem o Tecniquês

Transatlantic - Bridge Across Forever (2001)

Scope regularly seems to increase with reckless abandon

Why Talking About Risk Is Good

The optimal level of model complexity is at the minimum error rate on the validation set.

Methodology for supervised modeling.

Predicting the price of a stock three months in the future.

Double Tree as The Life

Why we have bought technology (cars, phones, etc.) from Korea

Sample Kanban Board

The Agile Iteration

Development Practices

Adapt

The Agile UX Designer

The Agile Project Manager

The Agile Tester

The Agile Programmer

The Agile Analyst

The Agile Customer

Quality is a team responsibility on an agile project

How Are Agile Projects Different?