In this presentation, Cameron Presley shows you how to implement basic LINQ Operations leveraging Funcs, Generics, and Extension Methods. Once fundamentals are in place, Cameron starts building the various LINQ methods
Este documento presenta el teorema de Cayley-Hamilton, el cual establece que el polinomio caracter鱈stico de una matriz A anula a A. Se demuestra aplicando propiedades de polinomios con coeficientes matriciales y la relaci坦n entre una matriz y su adjunta. Tambi辿n se presentan corolarios para operadores lineales y divisi坦n de polinomios.
El documento describe tres funciones trigonom辿tricas com炭nmente usadas: el arcocoseno, el arcotangente y el arcoseno. Explica que estas son las funciones inversas del coseno, tangente y seno respectivamente. Tambi辿n define el dominio y recorrido de la funci坦n arcoseno y algunas de sus propiedades como ser una funci坦n creciente e impar.
El documento describe la comunicaci坦n y el lenguaje como elementos esenciales para los seres humanos. Explica que la comunicaci坦n es el proceso mediante el cual compartimos informaci坦n con otros a trav辿s de expresiones y que el lenguaje nos permite estructurar signos para transmitir significados. Tambi辿n presenta modelos de comunicaci坦n y categoriza la comunicaci坦n seg炭n el emisor, receptor, medio, mensaje y contexto. En general, destaca que la comunicaci坦n es fundamental para la evoluci坦n humana ya que nos permite transmitir conocimientos y avanzar de forma colectiva.
This document discusses the SOLID principles of object-oriented design. It introduces each principle - Single Responsibility, Open/Closed, Liskov Substitution, Interface Segregation, Dependency Inversion - and provides examples of how to identify violations of the principles in code and refactor to improve code quality and maintainability. Specific refactoring techniques demonstrated include extracting classes, using factories and dependency injection, and defining role interfaces.
There are lots of talks about testing: they talk about syntax, methodologies, tools. But there is usually a missing point: Why it is important to do a test? What is important to test? What is not important to test? How to do testing?
There lots of examples in plnker just to see each step, and many surprises.
This talk is good for beginners, but also for some seasoned people that just want to light up some of the ideas that they might have been hatching.
Spoiler alert: testing will save you development time.
My playbook for when starting a new role as an engineer. If you're new to the industry or new to changing jobs, there's some helpful information and a game plan for how to be successful for your first week. You can find more information about this presentation at https://blog.thesoftwarementor.com/presentations
Learning postgresql, Chapter 1: Getting started with postgresql
Remarks
This section provides an overview of what postgresql is, and why a developer might want to use it.
It should also mention any large subjects within postgresql, and link out to the related topics. Since
the Documentation for postgresql is new, you may need to create initial versions of those related
topics.
Distributed System explained (with Java Microservices)Mario Romano
油
Since I've been working on distributed systems I always wanted to go back in time and teach myself what I know now, in order to avoid the silly mistakes I did. Things like vector clocks, the CAP theorem, how replication really works and why it's needed! This is the speech I'd needed when I wrote my first distributed system, and it's something you need to know if you fancy working in this area. In this talk you will understand these concepts using simple Java microservices talking to each other, using the three different architectures proposed by the CAP theorem. After a quick introduction to the theory, we will start looking at the code and running demos. Services will fall, the network will be partitioned... what will the winner architecture be?
Machine learning infrastructure solve data scientists' problems using infrastructure tools. This talk shows the case study of building SigOpt Orchestrate, an ML infrastructure tool. The talk highlights how data scientists' concerns as user mapped to solutions with some of today's most popular infrastructure tools.
To learn more about SigOpt Orchestrate: https://sigopt.com/orchestrate
Originally given as a talk for UC Berkeley's Women in Electrical Engineering and Computer Science group on January 24, 2019.
The Java Virtual Machine (JVM) can deliver significantly better performance through the use of Just In Time compilation. However, each time you start an application it needs to repeat the same process of analysis and compilation. This session discusses Java with Co-ordinated Checkpoint at Restore. This is a way to freeze an application and start it again (potentially many times) from the same checkpoint.
Back to Basics Webinar 3: Introduction to Replica SetsMongoDB
油
This document provides an introduction to MongoDB replica sets, which allow for data redundancy and high availability. It discusses how replica sets work, including the replica set life cycle and how applications should handle writes and queries when using a replica set. Specifically, it explains that the MongoDB driver is responsible for server discovery and monitoring, retry logic, and handling topology changes in a replica set to provide a consistent view of the data to applications.
This document discusses pointers in C++ and how they allow objects to communicate with each other. It provides an example of a light bulb and button class that illustrate this. The light bulb class tracks the state of the light and can change its state. The button class has a pointer to the light bulb object and can call the light bulb's method to change its state when pressed. This demonstrates how objects can talk to each other through the use of pointers, allowing the button object to modify the light bulb object.
1. The document discusses using Deeplearning4j and Kafka together for machine learning workflows. It describes how Deeplearning4j can be used to build, train, and deploy neural networks on JVM and Spark, while Kafka can be used to stream data for training and inference.
2. An example application is described that performs anomaly detection on log files from a CDN by aggregating the data to reduce the number of data points. This allows the model to run efficiently on available GPU hardware.
3. The document provides a link to a GitHub repository with a code example that uses Kafka to stream data, Keras to train a model, and Deeplearning4j to perform inference in Java and deploy the model.
Distributed Systems explained (with NodeJS) - Bruno Bossola, JUG TorinoCodemotion Tel Aviv
油
This document summarizes a presentation about distributed systems and NodeJS. It discusses key concepts like scalability, availability, consistency and the CAP theorem. It states that a distributed system cannot have all three of these properties and must choose two. The presentation demonstrates building three different types of distributed key-value stores in NodeJS - a CA system using two-phase commit, an AP system using sloppy quorums, and a CP system using majority quorums. Q&A links to resources on Amazon Dynamo, the RAFT consensus algorithm and the code used in the presentation.
Distributed System explained (with NodeJS) - Bruno Bossola - Codemotion Milan...Codemotion
油
Since I've been working on distributed systems I always wanted to back in time and teach myself what I know now, in order to avoid the silly mistakes I did! Things like vector clocks, the CAP theorem, how replication really works (and why it's needed), what BASE means and in general all about how this stuff really works! This is the speech I'd needed wheI wrote my first DT, and it's something you need to know if you fancy working in this area. And we will also be coding some very simple examples in NodeJS, as I am not a big believer of diagrams... show me code!
PL/SQL is a combination of SQL along with procedural programming features. It allows developers to perform operations on data in an Oracle database such as querying, inserting, updating, and deleting. Some key PL/SQL concepts include variables, conditions, loops, exceptions, triggers, stored procedures, and cursors. Cursors allow a program to retrieve multiple rows from a SQL statement and process them one by one.
I just made a change to the database schema, but now the team needs it for my feature to work. How can I keep track of my database changes and communicate them to the rest of the team? Migrations give a structured way to structurally alter your database structure as your application evolves . . . structurally. They also provide a way for everyone on the team: developers, testers, CI admins, DBAs, etc, to apply the latest changes wherever they are needed - with uniformity and low friction. Fluent Migrations for .NET provide a discoverable, human readable API that supports dozens of different databases (including SQL Server, PostgreSQL, Oracle). Topics covered in this session:
* Why you should use migrations
* How to write fluent migrations
* A look behind the scenes of how fluent migrations work
* Drawbacks/downsides to using migrations
* Other migration options for EF and NoSQL (Couchbase)
Ad hoc SQL scripts make you want to flip a desk? Keep your team on the same page with fluent migrations.
(This session will briefly mention EF Migrations, but is not primarily about EF).
This document provides an introduction to the Python programming language. It outlines the objectives of learning Python, which are to introduce the language, write code to automate tasks, and retrieve and use hydrologic data. The schedule for the week is also presented. Python is described as easy to learn, freely available, cross-platform, and widely used. The document then demonstrates basic Python concepts like arithmetic, strings, variables, lists, dictionaries, conditionals, loops, functions, and modules. It concludes by assigning a coding challenge for students to download USGS streamflow data and extract information from it using Python.
Automation for Anyone at Nutanix NEXT 2017 USChris Wahl
油
Are you wondering how to solve repetitive tasks with software automation, but you struggle every time you see the word developer or code? Do you know what APIs are and how they make these tasks easy to solve? In this session, well explore the framework that can apply to mundane tasks (i.e. PowerShell, Pester), and well discuss what open source tools are available to help solve these problems. Walk away with the advice you need to get started!
From Mess To Masterpiece - JFokus 2017Sven Ruppert
油
How a migration to MicroServices could change the team, architecture and coding culture. What you could you do and how you could transform a "Jurassic Park" into a lightweight environment. In this talk we will explore the strategy, techniques, pattern and tools I used to transform a team and the architecture that was grown over 15yrs. This will be a mix of pattern, tools and techniques that was able to migrate old systems, used inside insurance and banks. We had to migrate fat systems with a few million lines of code...
Solving Cross-Cutting Concerns in PHP - DutchPHP Conference 2016 Alexander Lisachenko
油
Talk about solving cross-cutting concerns in PHP at DutchPHP Conference.
Discussed questions:
1) OOP features and limitations
2) OOP patterns for solving cross-cutting concerns
3) Aspect-Oriented approach for solving cross-cutting concerns
4) Examples of using AOP for real life application
A simple explanation of basic principles of Distributed Programming with NodeJS. The CAP Theorem is fully explained, with working code the you can try yourself!
2012 07 making disqus realtime@euro pythonAdam Hitchcock
油
1) DISQUS implemented a real-time component to increase user engagement by getting new data to users quickly.
2) The architecture uses Redis for pub/sub messaging between frontend Flask servers using Gunicorn and gevent, and backend Python services that format and publish messages.
3) Testing was important to ensure the real-time system could handle DISQUS's large traffic, and metrics were used to measure and optimize performance.
Parallel Distributed Deep Learning on HPCC SystemsHPCC Systems
油
As part of the 2018 HPCC Systems Community Day event:
The training process for modern deep neural networks requires big data and large amounts of computational power. Combining HPCC Systems and Googles TensorFlow, Robert created a parallel stochastic gradient descent algorithm to provide a basis for future deep neural network research, thereby helping to enhance the distributed neural network training capabilities of HPCC Systems.
Robert Kennedy is a first year Ph.D. student in CS at Florida Atlantic University with research interests in Deep Learning and parallel and distributed computing. His current research is in improving distributed deep learning by implementing and optimizing distributed algorithms.
Taking a Gamble with Functional Domain ModelingCameron Presley
油
Presentation for Functional Domain Modeling where I cover how to identify/implement the domain for Blackjack. From there, we take a look at implementing various workflows by exploring the Maybe type!
Functional Programming Through Construction : First PrinciplesCameron Presley
油
This document discusses an approach to solving the Mars Rover Kata problem through functional programming principles. It begins by modeling the key nouns like Rover and Direction as immutable data. Functions are designed to map commands like "move forward" to actions that return a new Rover state. User input is mapped to commands and commands to actions through nested mappings. This composition allows separating concerns and building the solution incrementally. The approach emphasizes immutability, functions as mappings, and composition to reduce complexity and make the program easier to understand and debug.
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油
Since I've been working on distributed systems I always wanted to go back in time and teach myself what I know now, in order to avoid the silly mistakes I did. Things like vector clocks, the CAP theorem, how replication really works and why it's needed! This is the speech I'd needed when I wrote my first distributed system, and it's something you need to know if you fancy working in this area. In this talk you will understand these concepts using simple Java microservices talking to each other, using the three different architectures proposed by the CAP theorem. After a quick introduction to the theory, we will start looking at the code and running demos. Services will fall, the network will be partitioned... what will the winner architecture be?
Machine learning infrastructure solve data scientists' problems using infrastructure tools. This talk shows the case study of building SigOpt Orchestrate, an ML infrastructure tool. The talk highlights how data scientists' concerns as user mapped to solutions with some of today's most popular infrastructure tools.
To learn more about SigOpt Orchestrate: https://sigopt.com/orchestrate
Originally given as a talk for UC Berkeley's Women in Electrical Engineering and Computer Science group on January 24, 2019.
The Java Virtual Machine (JVM) can deliver significantly better performance through the use of Just In Time compilation. However, each time you start an application it needs to repeat the same process of analysis and compilation. This session discusses Java with Co-ordinated Checkpoint at Restore. This is a way to freeze an application and start it again (potentially many times) from the same checkpoint.
Back to Basics Webinar 3: Introduction to Replica SetsMongoDB
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This document provides an introduction to MongoDB replica sets, which allow for data redundancy and high availability. It discusses how replica sets work, including the replica set life cycle and how applications should handle writes and queries when using a replica set. Specifically, it explains that the MongoDB driver is responsible for server discovery and monitoring, retry logic, and handling topology changes in a replica set to provide a consistent view of the data to applications.
This document discusses pointers in C++ and how they allow objects to communicate with each other. It provides an example of a light bulb and button class that illustrate this. The light bulb class tracks the state of the light and can change its state. The button class has a pointer to the light bulb object and can call the light bulb's method to change its state when pressed. This demonstrates how objects can talk to each other through the use of pointers, allowing the button object to modify the light bulb object.
1. The document discusses using Deeplearning4j and Kafka together for machine learning workflows. It describes how Deeplearning4j can be used to build, train, and deploy neural networks on JVM and Spark, while Kafka can be used to stream data for training and inference.
2. An example application is described that performs anomaly detection on log files from a CDN by aggregating the data to reduce the number of data points. This allows the model to run efficiently on available GPU hardware.
3. The document provides a link to a GitHub repository with a code example that uses Kafka to stream data, Keras to train a model, and Deeplearning4j to perform inference in Java and deploy the model.
Distributed Systems explained (with NodeJS) - Bruno Bossola, JUG TorinoCodemotion Tel Aviv
油
This document summarizes a presentation about distributed systems and NodeJS. It discusses key concepts like scalability, availability, consistency and the CAP theorem. It states that a distributed system cannot have all three of these properties and must choose two. The presentation demonstrates building three different types of distributed key-value stores in NodeJS - a CA system using two-phase commit, an AP system using sloppy quorums, and a CP system using majority quorums. Q&A links to resources on Amazon Dynamo, the RAFT consensus algorithm and the code used in the presentation.
Distributed System explained (with NodeJS) - Bruno Bossola - Codemotion Milan...Codemotion
油
Since I've been working on distributed systems I always wanted to back in time and teach myself what I know now, in order to avoid the silly mistakes I did! Things like vector clocks, the CAP theorem, how replication really works (and why it's needed), what BASE means and in general all about how this stuff really works! This is the speech I'd needed wheI wrote my first DT, and it's something you need to know if you fancy working in this area. And we will also be coding some very simple examples in NodeJS, as I am not a big believer of diagrams... show me code!
PL/SQL is a combination of SQL along with procedural programming features. It allows developers to perform operations on data in an Oracle database such as querying, inserting, updating, and deleting. Some key PL/SQL concepts include variables, conditions, loops, exceptions, triggers, stored procedures, and cursors. Cursors allow a program to retrieve multiple rows from a SQL statement and process them one by one.
I just made a change to the database schema, but now the team needs it for my feature to work. How can I keep track of my database changes and communicate them to the rest of the team? Migrations give a structured way to structurally alter your database structure as your application evolves . . . structurally. They also provide a way for everyone on the team: developers, testers, CI admins, DBAs, etc, to apply the latest changes wherever they are needed - with uniformity and low friction. Fluent Migrations for .NET provide a discoverable, human readable API that supports dozens of different databases (including SQL Server, PostgreSQL, Oracle). Topics covered in this session:
* Why you should use migrations
* How to write fluent migrations
* A look behind the scenes of how fluent migrations work
* Drawbacks/downsides to using migrations
* Other migration options for EF and NoSQL (Couchbase)
Ad hoc SQL scripts make you want to flip a desk? Keep your team on the same page with fluent migrations.
(This session will briefly mention EF Migrations, but is not primarily about EF).
This document provides an introduction to the Python programming language. It outlines the objectives of learning Python, which are to introduce the language, write code to automate tasks, and retrieve and use hydrologic data. The schedule for the week is also presented. Python is described as easy to learn, freely available, cross-platform, and widely used. The document then demonstrates basic Python concepts like arithmetic, strings, variables, lists, dictionaries, conditionals, loops, functions, and modules. It concludes by assigning a coding challenge for students to download USGS streamflow data and extract information from it using Python.
Automation for Anyone at Nutanix NEXT 2017 USChris Wahl
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Are you wondering how to solve repetitive tasks with software automation, but you struggle every time you see the word developer or code? Do you know what APIs are and how they make these tasks easy to solve? In this session, well explore the framework that can apply to mundane tasks (i.e. PowerShell, Pester), and well discuss what open source tools are available to help solve these problems. Walk away with the advice you need to get started!
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How a migration to MicroServices could change the team, architecture and coding culture. What you could you do and how you could transform a "Jurassic Park" into a lightweight environment. In this talk we will explore the strategy, techniques, pattern and tools I used to transform a team and the architecture that was grown over 15yrs. This will be a mix of pattern, tools and techniques that was able to migrate old systems, used inside insurance and banks. We had to migrate fat systems with a few million lines of code...
Solving Cross-Cutting Concerns in PHP - DutchPHP Conference 2016 Alexander Lisachenko
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Talk about solving cross-cutting concerns in PHP at DutchPHP Conference.
Discussed questions:
1) OOP features and limitations
2) OOP patterns for solving cross-cutting concerns
3) Aspect-Oriented approach for solving cross-cutting concerns
4) Examples of using AOP for real life application
A simple explanation of basic principles of Distributed Programming with NodeJS. The CAP Theorem is fully explained, with working code the you can try yourself!
2012 07 making disqus realtime@euro pythonAdam Hitchcock
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1) DISQUS implemented a real-time component to increase user engagement by getting new data to users quickly.
2) The architecture uses Redis for pub/sub messaging between frontend Flask servers using Gunicorn and gevent, and backend Python services that format and publish messages.
3) Testing was important to ensure the real-time system could handle DISQUS's large traffic, and metrics were used to measure and optimize performance.
Parallel Distributed Deep Learning on HPCC SystemsHPCC Systems
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As part of the 2018 HPCC Systems Community Day event:
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Robert Kennedy is a first year Ph.D. student in CS at Florida Atlantic University with research interests in Deep Learning and parallel and distributed computing. His current research is in improving distributed deep learning by implementing and optimizing distributed algorithms.
Taking a Gamble with Functional Domain ModelingCameron Presley
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Presentation for Functional Domain Modeling where I cover how to identify/implement the domain for Blackjack. From there, we take a look at implementing various workflows by exploring the Maybe type!
Functional Programming Through Construction : First PrinciplesCameron Presley
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This document discusses an approach to solving the Mars Rover Kata problem through functional programming principles. It begins by modeling the key nouns like Rover and Direction as immutable data. Functions are designed to map commands like "move forward" to actions that return a new Rover state. User input is mapped to commands and commands to actions through nested mappings. This composition allows separating concerns and building the solution incrementally. The approach emphasizes immutability, functions as mappings, and composition to reduce complexity and make the program easier to understand and debug.
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9. @pcameronpresley
Set of operations that works on data
independent of the source
In addition, these operations are type safe,
allowing the compiler to catch your
mistakes sooner
9
25. @pcameronpresley
Background
Introduced in C# 3.0
Extends functionality to types without
having to recompile or creating a new
type
Great for when working with types you
dont have access to
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28. @pcameronpresley
The most common extension methods
are the LINQ standard query operators
that add query functionality to the
existing System.Collections.IEnumerable
and
System.Collections.Generic.IEnumerable
<T> types.
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MS Docs on Extension Methods
48. @pcameronpresley
Background
Returns a subset of a collection based on a
predicate
Length is between 0 and original length
Doesnt return items that werent in the
list
Maintains order
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68. @pcameronpresley
Use Reduce to Transform a
Collection to a Single Value by
First Identifying the Initial
Value, Followed by Writing
the Combining Logic
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