Data Collection and Pre-processing

The first step in building a machine learning model is to collect and prepare the data. Data is the fuel that powers machine learning models, and without high-quality data, you cannot build a high-quality model. There are several key considerations when collecting data for a model, including type and source of data, data format, and data volume. Before collecting data, you should determine how much data you need. While more data is always better, you need to ensure that collecting and pre-processing the data does not take longer than the model’s expected lifespan. Most machine learning models are built to make predictions for a specific timeframe. After that timeframe, the model’s accuracy will begin to degrade.

Feature Engineering

Once you have collected and prepared your data, you need to transform it into a format that can be used by the machine learning model. This is known as feature engineering, and it is an important part of the modeling process. There are three main considerations when feature engineering your data: univariate transformation, selection of relevant features, and transformation of categorical variables. Univariate transformation is the process of converting continuous variables, such as age and weight, into new categorical variables, such as age groups and weight groups. In most modeling scenarios, continuous variables are binned into groups to make them easier to use in the model. Selecting relevant features is important because the model will use these features to make predictions. You want to ensure that the features are relevant to your modeling scenario to avoid misleading predictions and false positives. Finally, transformation of categorical variables is important because machine learning models perform better with categorical variables than with raw numbers.

Model Selection

Once you have selected the data you want to use and transformed it into the format needed by the model, you need to select the appropriate model. A wide variety of machine learning models can be used to solve a wide variety of problems. The first step in selecting a model is determining which type of model you want to use. There are three main types of machine learning models: These three models each have unique strengths and weaknesses, and each model can be used to solve a variety of problems. Once you have selected a model type, you need to identify the best model for your specific problem. The model with the highest accuracy does not always win. You need to assess the model’s error rate, the interpretability of the model, and the time needed to train the model. In some cases, it may be better to use a model with a lower accuracy rate if it has a lower error rate, provides better insights, or can be trained faster.

Model Training

After you have selected the model and prepared the data, you are ready to train the model. During training, the model is given the prepared data along with the expected outcomes. The model uses this data to uncover patterns and make predictions. While there are many techniques for training a machine learning model, most models are either trained using an online or offline approach. Online models use parallel processing and can be used to predict multiple outcomes in near real time. Offline models use serial processing and can be used to make predictions offline. The best approach to use depends on the model and the problem being solved. While there are many different techniques for training a machine learning model, there are three key considerations that should be evaluated during each training session. The first consideration is model accuracy. You want to ensure that the model is accurately uncovering patterns and making accurate predictions. You can use a variety of metrics, including accuracy, ROC, and AUC, to ensure that the model is performing well. The second consideration is model bias and variance. Bias is the tendency of the model to consistently predict a specific outcome. Variance refers to the range of values the model is predicting. You want to ensure that the model is neither too biased nor too inconsistent.

Model Evaluation

After the model has been trained, you can evaluate the accuracy of the model by testing it against a holdout dataset. A holdout dataset is a portion of the data that was not used during training. The model can be tested against a new, completely unrelated dataset to determine how well it generalizes. There are three key considerations when evaluating the model. The first consideration is model accuracy. You want to ensure that the model is accurately predicting the outcomes in the holdout dataset. You can use a variety of metrics, including accuracy, ROC, and AUC, to ensure that the model is performing well. The second consideration is model variance. You want to ensure that the model is not too inconsistent. You can use a model’s standard deviation and coefficient of variation to determine how consistent the model is. The third consideration is model interpretability. You can use a variety of techniques to assess model interpretability, including t-tests and R2 values.

Model Deployment

After you have selected the model and trained it, you are ready to deploy it. There are many considerations when deploying a machine learning model, including model type, cost, and maintenance requirements. You also need to consider who will use the model and how it will be deployed. Once you have selected the model type, you can use that model to solve a variety of problems. If you follow these steps, you will have the skills you need to create your own machine learning prediction model. With dedication, you can create a model that can make accurate predictions and transform any industry.

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Object-oriented programming is a rather complex subject in PHP. This makes it difficult for new programmers to understand PHP OOP, especially if they don’t have much programming experience.

Object-oriented programming appeared in PHP 4, but it gained momentum with PHP 5. In version 5, the PHP object model was rewritten to improve features and performance, and to introduce a complete object model for php classes.

What is object-oriented programming?
Object-oriented programming is a style of programming based on the concept of objects. It helps developers, prevents reinventing the wheel, and makes code easy to maintain and scale.

At first, object-oriented programming seems incomprehensible, but when you dig deeper, you’ll realize that it’s designed to simplify programming.

Why use object-oriented programming?
There are various advantages to using PHP OOP over procedural programming in PHP, such as:

Code reuse and rework: let’s say you want to build a Mercedes car object, and your friends want to build an Audi car object. You build your objects, but you discover that both objects have a lot in common between Mercedes and Audi, like the number of tires. In fact, both are cars. So instead of creating the two objects separately from scratch, if you have one class of cars with common properties and methods, you can save a lot of repetition by reusing and reworking the code.

Modularity: if you create several separate classes for different entities, you make them modular, and if you want to fix something, you only need to edit that particular class, not the others. This modularity turns out to be useful in troubleshooting.

Scalability: Object-oriented programs are more scalable than structured programs. The object interface provides all the information needed to replace an object, making it easy to replace old code or add new code to scale in the future.

Maintenance: programs are improved regularly with many changes. An object-oriented program is much easier to modify and maintain than an undirected program.

The concept of classes and objects
What is a class and object in PHP OOP?
Before we delve into the world of object-oriented programming, let’s learn about PHP classes and objects, which are the foundation of the PHP OOP paradigm.

A class is a data type defined by the programmer that contains various data types as well as various functions.

An object is an instance of a class. The object gets a copy of all the data and functions in the class, so it acts as an independent entity.

What are properties and methods?
Properties in a class are variables that can store data of different data types. A method is a function defined within a class.

All objects created in that class get a copy of that variable property and a copy of all member functions known as methods.

How do we create a class and an object?
In a class, we group the code that handles a certain topic. Thus, we must use a single noun like Car to name the class, which will handle logic about cars.

The syntax to create a class is very simple and straightforward. You must use the keyword class to declare the class followed by the name of the class.

• Declare a class using the keyword class.
• Use a singular noun and use the first letter.
• If the class name contains more than one word, then capitalize each word using the so-called CamelCase style spelling. For example: JapaneseCar, AmericanCar.
• A class instance is an object created from an existing class.
• new is used to create an object from a class.

Now you can very easily create an object from a class using the keyword new.

How to define properties in a class?
Properties or member variables are used to add and store data in a class. Properties can store values of data types – strings, integers, decimals, logical values, etc. They are just like regular variables, but they are associated with an object instance, and thus you can only access a variable with an object.

Constructor and destructor
There are several methods known as magic methods in PHP. Among them the two most important magic methods are __construct and __destruct. These two methods create a constructor and a destructor for the class. Remember, magic methods always start with two underscores.

What is a constructor and a destructor?

The __construct method is a method that is called by the class when it creates an object. It is used to prepare a new object for use. Constructors can be used to assign parameter values to object properties.

The __destruct method is a function that is called by the class when the object is destroyed. It is usually used to clear memory when an object is destroyed.

Visibility Assignment in PHP
Earlier we discussed the use of one of the keywords public, private and protected when defining a property or method. Public, Protected and Private are the three types of visibility in PHP for controlling access to properties, variables or methods.

Public: a public method or variable is available everywhere.
Private: if a variable property or method is private, then it is only accessible within the class. For example: if the color property of the Car class is private, then you cannot access it outside the class like – echo $bmw->color; but a method like getColor can access it because it is inside the class.
Protected: if a property variable or method is protected, it can be accessed from inside the class or from any class that inherits from that class.
Why shouldn’t we use public visibility all the time?

Because it is not all that safe to keep everything publicly visible. To make it safe, PHP OOP introduced these different features.

Static properties and methods
A static method or property can be accessed without having to create an instance object. Simply use the class name, the scope resolution statement, and the property or method name.

We’ve already studied three modifiers: private, protected, and public. Static is the fourth access modifier in PHP OOP that allows you to access properties and methods without having to create objects from classes.

Conclusion
PHP OOP offers many advantages over procedural programming and provides an easier approach to building complex web applications with easier scalability.

You are now familiar with the style of object-oriented programming and should have a clear understanding of the basic concepts of PHP OOP, i.e. object-oriented programming.

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Focus on the scope of the language
At university, immersion in programming is gradual, and during the study you can get acquainted with several languages. But often universities don’t keep up with trends and don’t teach new technologies that are actively used in development. Internships or courses from IT companies help students better understand what is happening in IT.

If you decide to change careers and start learning programming from scratch, first decide what exactly you would be interested in doing. Any programming language is just a tool to get things done. Start by choosing a direction in IT that intersects with your interests and abilities. Maybe you’ve been following a particular technology or a particular field for a long time. Maybe you’re more attracted to mobile app development than to websites, or you want to create computer games.

Programming is used in almost every field, so it’s hard to list all the options. It is possible to distinguish the main directions of development depending on the purpose of the software and the devices for which it is created. Some of them use several programming languages, and somewhere a specific set of technologies prevails.

System and firmware

To write a driver, an operating system, or work on smart home devices, you need to learn system programming. Basically it uses low-level languages that address the computer hardware almost directly. The most common ones are C++, C.

Web applications

The applications you open with your browser, from social networks to online stores, are written by web developers. Front-end developers create the user part in JavaScript, HTML and CSS. Backend-developers are responsible for the server side and implement the intended application logic. Among the most common languages for back-end – PHP, Python, C#, Ruby, Java, Go, Perl. There are programmers who know the technologies for both parts of the application – they are called full-stack developers.

Mobile applications

Mobile devices are not just smartphones and tablets, but also wearable electronics. But development is dominated by two operating systems – Android and iOS. For the first one, Objective-C and Swift are usually used, and for the second one, Java and Kotlin are used. It is also possible to develop cross-platform mobile applications that are suitable for Android and iOS. To do this, you need to learn special platforms, such as Cordova, Xamarin, and Flutter.

Desktop applications.

Microsoft Word, Excel are well known examples of desktop applications that work without the Internet resources of the operating system. Today there are more products for working in browsers and on mobile devices. But in some areas desktop applications are still relevant and in demand. As a rule, complex scientific software, tools for professional video and audio processing, many computer games are developed for desktops. The languages Swift, C#, C, C++, Python, Ruby and also JavaFX can be considered for this direction.

Assess the demand for the language
When you have decided on the scope of the language, it is important to consider its prospects in the labor market. If it’s in demand, there will be more job openings, which means the chances of getting your first job sooner. Also, the popularity of the language shows that there is an active community of developers who are interested in its development and support.

There are various rankings that evaluate the popularity of programming technologies. For example, every month the TIOBE index is updated – a list of languages that are most frequently mentioned in search queries. The top 5 usually share C, Python, Java, C++, and C#.

RedMonk’s ranking is based on data from the largest developer communities on GitHub and Stack Overflow. The August 2021 Top 5 includes JavaScript, Python, Java, PHP, and CSS.

In 2021, the Stack Overflow community released a large Developer Survey, for which they surveyed over 83,000 respondents from 181 countries. It turned out that programmers themselves like Rust the most, while COBOL is considered the most intimidating.

The study has data that the highest salaries are in programmers who write in Clojure, F#, Elixir, Erlang, Perl, Ruby, Scala, Rust, Go, LISP. It turns out that popular technologies are not the highest paid at all. The top 5 languages are used in narrow spheres and in general the demand for such programmers is lower than in web or mobile development. Most likely, it is the shortage of developers that increases the competition for them and the level of salaries.

There is not such a significant difference in pay between the popular and the highest paid languages to make a choice solely because of this criterion. As a rule, a programmer earns more with experience, and at the beginning of the career, regardless of the language salaries will be about the same.

Learn about the peculiarities of learning a language
You can master programming with any background, both technical and humanities. But for some, self-study will be enough, and some will be more suited to studying on a course with a mentor. It is worth checking out what training options are available for the chosen language.

Popular languages like Java, Python, PHP are generally similar. To learn such a programming language and become a junior developer, it will take about a year. Most courses are designed for about this period. It is possible to accelerate a little training, if a day to devote a couple of hours to programming, and move from theory to practice, start to do some projects by themselves, at least for personal purposes.

During the programmer needs not only the language itself, but also the whole ecosystem of technology. And after learning the basics, it is better to devote time to mastering frameworks, libraries, databases and other tools.

Why programmers need to know several languages
At the start of training, you can try to understand several languages to choose one. But you should not learn several languages in parallel. This will not increase the chances of finding a job. Developers are valued for relevant and applied knowledge in their stack, and a broad technical outlook comes only with experience.

Practicing programmers find it easier to learn a new language. Usually, the transition from one language to another is accompanied by a decrease in salary. This is connected with the fact that the programmer will not have experience working on commercial projects in the new stack, and will have to apply for a lower position, for example, not senior, but middle or junior developer. Such transition is possible within one company without any loss of money, when it is possible to use both technologies on the project to develop skills and gain experience.

It seems that the choice of the first programming language is too responsible step. What if you spend a year learning it and end up disappointed in your choice? In fact, whatever language you choose, the important thing is that you start learning programming. And if over time you even want to change your specialization, with experience in commercial development it will be much easier to do it.

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And this is in fact true, but in order to clearly understand what T-SQL is, you must first understand what a relational database and the SQL language are essentially.

So first we will go through all the basic concepts and learn all the necessary information that will lead you smoothly to a clear understanding of what T-SQL is.

What is a database
A database is any set of information that is stored in a certain way, for the purpose of further using that information.

However, if we talk about databases that are used in information systems on computers, we will, of course, be talking about the so-called relational databases.

A relational database is ordered information connected to each other by certain relationships. It is presented in the form of tables, which are all this information.

At the heart of the relational model is the theory of sets, which implies the union of different objects into one whole, under one whole in the database is precisely what is meant by a table.

Note! The normalization of databases in simple words.

What is a DBMS
We found out that a database is an ordered set of information, but here another question arises, and how all this information looks physically on the computer?

And it is represented, of course, in the form of files, formed in a special format.

So the next question arises, how do you create such a file and open it in order to view all the information, in other words, how do you create a database and manage all the information in the database?

To do this, there must be a tool, i.e. a special program. And such a program is a DBMS – a database management system, abbreviated DBMS.

On their capabilities and popularity, we can distinguish the following DBMS:

• Microsoft SQL Server;
• Oracle Database;
• MySQL;
• PostgreSQL.

What is SQL

Now we understand that the information in a relational database is ordered and logically represented in the form of tables, and all this information is stored and managed by a special program called a DBMS.

But how can we access and manipulate the data? In other words, how do we get information out of the database, how do we add, remove or change information in the database?

To do this, there must be a special mechanism that allows us to manipulate data. And this is precisely the mechanism of the SQL language.

SQL (Structured Query Language) is a structured query language, using this language to write special queries to the database in order to retrieve these data and manipulate them.

What is T-SQL

SQL language is a standard, it is implemented in all relational databases, but each database has an extension of this standard, a so-called dialect of SQL language.

And so we’re getting to the heart of our question today – what is T-SQL.

T-SQL is an extension of the SQL language implemented in Microsoft SQL Server.

T-SQL is an abbreviated name for the language, and the full name is Transactional SQL.

T-SQL has all the features of SQL, but it is designed to solve the problems of programming, not related to relational data. In other words, in T-SQL you can fully program using variables, loops, conditional structures and other features. T-SQL allows us to implement complex business logic algorithms in the form of stored procedures and functions, thereby creating so-called “programs” inside the database.

In addition, T-SQL simplifies writing SQL queries due to the huge number of built-in system functions, and allows you to administer SQL Server and get system information using system views, procedures and functions.

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