Learn to Git: Basic Concepts

Relationship of Estimation Dimensions

The Good and the Bad News for Artificial Expertise

Algorithmic Vs. Al Problem Solving

Spiral Model

The Waterfall Cycle Never Exists! (notice the backward arrows)

Iterative development produces the architecture first,

Effective Deployment of 6 Best Practices

The Rational Unified Process describes how to effectively deploy commercially proven approaches to software development for software development teams. These are called “best practices” not so much because you can precisely quantify their value, but rather, because they are observed to be commonly used in industry by successful organizations. The Rational Unified Process provides each team member with the guidelines, templates and tool mentors necessary for the entire team to take full advantage of among others the following best practices:

1. Develop software iteratively
2. Manage requirements
3. Use component-based architectures
4. Visually model software
5. Verify software quality
6. Control changes to software

Develop Software Iteratively  Given today’s sophisticated software systems, it is not possible to sequentially first define the entire problem, design the entire solution, build the software and then test the product at the end. An iterative approach is required that allows an increasing understanding of the problem through successive refinements, and to incrementally grow an effective solution over multiple iterations. The Rational Unified Process supports an iterative approach to development that addresses the highest risk items at every stage in the lifecycle, significantly reducing a project’s risk profile. This iterative approach helps you attack risk through demonstrable progressfrequent, executable releases that enable continuous end user involvement and feedback. Because each iteration ends with an executable release, the development team stays focused on producing results, and frequent status checks help ensure that the project stays on schedule. An iterative approach also makes it easier to accommodate tactical changes in requirements, features or schedule.

Manage Requirements  The Rational Unified Process describes how to elicit, organize, and document required functionality and constraints; track and document tradeoffs and decisions; and easily capture and communicate business requirements. The notions of use case and scenarios proscribed in the process has proven to be an excellent way to capture functional requirements and to ensure that these drive the design, implementation and testing of software, making it more likely that the final system fulfills the end user needs. They provide coherent and traceable threads through both the development and the delivered system.

Use Component-based Architectures  The process focuses on early development and baselining of a robust executable architecture, prior to committing resources for full-scale development. It describes how to design a resilient architecture that is flexible, accommodates change, is intuitively understandable, and promotes more effective software reuse. The Rational Unified Process supports component-based software development. Components are non-trivial modules, subsystems that fulfill a clear function. The Rational Unified Process provides a systematic approach to defining an architecture using new and existing components. These are assembled in a well-defined architecture, either ad hoc, or in a component infrastructure such as the Internet, CORBA, and COM, for which an industry of reusable components is emerging.

Visually Model Software  The process shows you how to visually model software to capture the structure and behavior of architectures and components. This allows you to hide the details and write code using “graphical building blocks.” Visual abstractions help you communicate different aspects of your software; see how the elements of the system fit together; make sure that the building blocks are consistent with your code; maintain consistency between a design and its implementation; and promote unambiguous communication. The industry-standard Unified Modeling Language (UML), created by Rational Software, is the foundation for successful visual modeling.

Verify Software Quality  Poor application performance and poor reliability are common factors which dramatically inhibit the acceptability of today’s software applications. Hence, quality should be reviewed with respect to the requirements based on reliability, functionality, application performance and system performance. The Rational Unified Process assists you in the planning, design, implementation, execution, and evaluation of these test types. Quality assessment is built into the process, in all activities, involving all participants, using objective measurements and criteria, and not treated as an afterthought or a separate activity performed by a separate group.

Control Changes to Software  The ability to manage changemaking certain that each change is acceptable, and being able to track changesis essential in an environment in which change is inevitable. The process describes how to control, track and monitor changes to enable successful iterative development. It also guides you in how to establish secure workspaces for each developer by providing isolation from changes made in other workspaces and by controlling changes of all software artifacts (e.g., models, code, documents, etc.). And it brings a team together to work as a single unit by describing how to automate integration and build management.

Six Sigma

Earned Value System

Cleanroom Software Engineering

K-means: Common choices for proximity, centroids, and objective functions.

Different types of clusters as illustrated by sets of two-dimensional points.

Agglomerative Hierarchical Clustering

Full Stack

General Approach to Solving a Classification Problem

A classification technique (or classifier) is a systematic approach to building classification models from an input data set. Examples include decision tree classifiers, rule-based classifiers, neural networks, support vector machines, and na ̈ıve Bayes classifiers. Each technique employs a learning algorithm to identify a model that best fits the relationship between the attribute set and class label of the input data. The model generated by a learning algorithm should both fit the input data well and correctly predict the class labels of records it has never seen before. Therefore, a key objective of the learning algorithm is to build models with good generalization capability; i.e., models that accurately predict the class labels of previously unknown records. 

Da imobilização à internalização da mudança

Classification

Classifying an unlabeled vertebrate. The dashed lines represent the outcomes of applying various attribute test conditions on the unlabeled vertebrate. The vertebrate is eventually assigned to the Non-mammal class. 

Training and test error rates

Notice that the training and test error rates of the model are large when the size of the tree is very small. This situation is known as model underfitting. Underfitting occurs because the model has yet to learn the true structure of the data. As a result, it performs poorly on both the training and the test sets. As the number of nodes in the decision tree increases, the tree will have fewer training and test errors. However, once the tree becomes too large, its test error rate begins to increase even though its training error rate continues to decrease. This phenomenon is known as model overfitting.