DEV Community: Artemiy Gazizyanov

How to start with Machine Learning?

Artemiy Gazizyanov — Thu, 28 Nov 2019 08:50:29 +0000

The first man, who used the term ML(Machine Learning) was Arthur Samuel in 1959.

"A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E."

You can hardly understand something from this definition. So, let’s go deeper.🤔

Where is Machine Learning used?

ML can be used everywhere.

For example, you want to predict the cost of the car, according to different parameters like: colour, condition of a vehicle body and interior, the number of accidents of this car, etc.
It's hard for a human to process this set of data, because there can be a lot of parameters. You may ask: "What can I do in this situation - I have 10000 cars, and I don’t want to spend my time on this."

You can ask machine learning for help.😊

What do I need for Machine Learning?

Create a model. The first thing you need to make your machine predict the result according to the input data, it is the input data.

Collect training data. They can be taken from anywhere. They can be assembled manually, which, apparently, leads to fewer errors, but it can be done automatically.

Train the model. The more varied training data are, the more precedents the machine observes. Therefore, the easier it is to find patterns and the more accurate the result is.

Algorithm. One task can be resolved in many ways. That's why you should properly choose the one algorithm. The speed of the model's work and the accuracy of its predictions fully depend on the algorithm.

But, I’m new in Machine Learning, how can I start?.
I`ve searched across the internet to find a good guideline. There are a lot of different purposes to learn ML, so I have notes down ones I like.

Quick Guide on Machine Learning for you

Step 1 – Basics

Machine learning is closely related to Linear Algebra, Statistics and Python.

Linear Algebra. Frankly, you need only the basic understanding in Linear Algebra, because most of the math algorithms are already included in different libraries. In opposite, if you want to develop your own algorithm from scratch you should study Linear Algebra and Multivariate Calculus.

Statistics. Machine learning is built on data.
Most of the time you will search the right data sets. Therefore, you need to know at least the basics of statistics. You should take a look at key concepts in statistics, like Statistical Significance, Probability Distributions, Hypothesis Testing, Regression, etc.

Python. It is a programming language, which is as popular right now as ML is. This language has a huge number of libraries for ML and a big community, so you can find answers to your questions in most cases.

Step 2 – Terminology

Model – a kind of representation learned from data by applying some machine learning algorithm.
Feature – an individual measurable property of the data. A set of features can be described as a feature vector. Feature vectors are the input to the model. For example, in order to predict car’s price, there may be features like colour, size, car condition, etc.
Target (Label) – a variable or a label is the prediction to be made by the model. For the car’s price example, the label with each set of input would be the name of the brand like BMW, Mercedes, Ford, etc.
Training – process when we give a set of inputs(features) and it’s expected outputs(labels). This all you need to create a model that will map new data to one of the categories trained on.
Prediction – the result, which we get after the model is trained.

Step 3 – Types of Machine Learning

The classical education is divided into instruction with and without a teacher.

Supervised Learning. Learning with a teacher is always some kind of training data set – the set on which the model is trained.

Unsupervised Learning. Learning without a teacher does not contain any output. The machine is simply given gigabytes of data so it tries to find hidden patterns and put everything in order.

I can talk about the following algorithms more in my future posts if you ask me about this.

Reinforcement learning
Linear Regression
Logistic Regression
Decision Tree
SVM
Naive Bayes
kNN
K-Means
Random Forest
Dimensionality Reduction Algorithms
Gradient Boosting algorithms
Deep learning
Ansamble methods

Step 4 – How to Practice Machine Learning?

You need to learn various models and practice on real datasets. By doing this, you will understand which type of algorithms resolve the problem more accurate.
You need to learn how to collect data, how to integrate, clean and process it.

Step 5 – Resources for Learning Machine Learning

There are various online and offline resources and courses, but which one is the best?

If you know good books or course, please share in the comments, lets finish this guide together!👇👇👇

Not to be a snail, use AMP HTML email 🐌

Artemiy Gazizyanov — Tue, 26 Nov 2019 14:11:00 +0000

As you may know, Google announced AMP HTML email, which can be very useful to increase email’s performance. I want to shed light on this feature in Aspose.Email.

What is AMP HTML for email?

Imagine, if emails could provide dynamic content, with the ability to update data included in emails? 😊
As you know, email messages are static and don’t change after they were sent. But, in the fast-pacing world of technologies, we are used to rapid progress. So, it's time for email messages to change too!
With AMP HTML email, its content can be updated after the email was sent, ensuring timeliness and relevancy.

AMP (Accelerated Mobile Pages) is a developer’s package from Google for developing a lightweight system with more rapid loads. AMP is a framework made up with HTML, JavaScript and CSS - a standard to create user-first web content.

Why AMP HTML for email?

APM HTML technology is based on web technologies, so you won’t get lost in it. It provides own validator and a set of custom elements to empower basic HTML.

Using AMP HTML email allows to increase the interactivity of your messages and add more usability. Now you can do some actions within the email interface, like: fill out questionnaires or schedule appointments, add photo carousels, include last news and RSVP to an online event, such as meetings or webinars, etc.

Speed up emails with AMP HTML

By using parts of Google’s AMP Project for email, Aspose.Email increases messages download speed, that is especially critical while working with mobile users.

AMP HTML also gives applications a way to cache and serve content with great efficiency.
You can see the code snippet, which demonstrates creating, saving, and updating AMP Emails using Aspose.Email API here. 👈

Aspose.Email API, also allows you to manipulate email storages, and to use this functionality you don’t need to install any other dependencies.

Questions time.

👇👇👇Please share your thoughts in the comments below.👇👇👇
Do you already use AMP HTML emails?

Export Lotus Notes (.NSF) messages with Aspose.Email

Artemiy Gazizyanov — Wed, 20 Nov 2019 12:12:08 +0000

What is IBM Notes?

IBM (Lotus) Notes and IBM Domino are the client and server, which represents a collaborative client-server software platform. IBM Notes and Domino is a distributed document-oriented NoSQL database and messaging framework and a rapid application development environment that includes pre-built applications like email, calendar, and others. IBM Notes differs from its primary commercial competitors, like Microsoft Exchange, which are purpose-built applications for mail and calendaring that offer APIs for extensibility. The history of IBM Notes is spanning more than 30 years.

What does Lotus consist of?

IBM Notes provides plenty of useful functions, such as:

Email
Calendars
To-do lists
Contact management
Discussion forums
File sharing
Microblogging
Instant messaging
Blogs
User directories

Why did people choose it?

Lotus Notes was one of the first applications providing business collaboration functions. When it was published in the 90s, it became an instrumental in turning "chat groups" and "message boards" into the right online collaboration workspaces as we know it now.

By the way, before HTTPS was even invented, Lotus Notes provided its authentication certificate for connecting to online data sources with encryption, which is called Lotus Notes ID. Therefore, Lotus Notes applications and databases were encrypted and could only be used by authorized users by their Notes ID.

Replication of Lotus Notes allowed keeping multiple copies of databases on various servers and local machines. It allowed developers to create rich text databases with variable length data records.

So, we can highlight two main reasons why people were choosing it:

Security. IBM Notes Domino scales down security risks for an organization more than MS Office does. As we know, MS Office attracts hackers with Office macros allowing malicious scripts that may run in Office to trigger crypto viruses or locally stored malware. Some people admit that IBM Domino is more secure, and others claim that now it is not popular enough to attract hackers' attention. The point is that using IBM Notes Domino is safer compared to MS Office.
Stability. Lotus IBM Notes has a long history on the market. This software solution has remained stable for over 20 years, whick means that companies that have invested in working with this product can be calm about their investments.

Why do people move from IBM Notes?

If everything is so good, you may ask, "Why people move from IBM Notes?".
There are some reasons for that:

The high cost of IBM Lotus Notes solution.
I have found a chat message branch from 1997. And there is one main disadvantage that was accurate with Domino Server more than 20 years ago – large consumption of RAM. Also, Lotus Notes requires more space on the system comparing with MS Outlook.
Problems with multitasking. For example, if you try to sort a view in NSF file with 1000000 documents and read the mail while the sort finished, it can become "mission impossible" as it cannot be done at the same time.
Problems with Lotus Notes Calendar. If you receive many messages a day, you can miss an appointment, and you will miss a meeting. Because if you do not accept a meeting invite, it never shows up in the calendar view. You have to create a separate folder for meeting responses. If you accidentally delete the calendar document or response document – everything will disappear.
Popularity. Comparing IBM Notes with MS Office, we can admit that Microsoft's solution is much more popular.
IBM Notes doesn't look user-friendly. More and more users are familiar with the Microsoft solution. This fact impacts on the speed of onboarding and degree of overall efficiency. New employees don't have to learn how to set a calendar appointment or send an email, which increases the productivity of the company. Some administrators find Notes Domino hard to administrate.
Integration issues. SaaS model is very popular nowadays. There are many great tools available for many aspects of business. The greatest thing about SaaS is that it easily integrates with large software tools. If you are using IBM Notes server Domino, it can be a challenge to set up integration between the server and SaaS.
Configuration. Other platforms come with a good central management right out of the box, while you have to spend a lot of time to configure IBM Notes Domino.

Moving Mailbox from IBM Notes.

All the abovementioned points force to migrate from IBM Notes. And the first step - is migrating messages.

All messages are stored in NSF storage, which is initial storage in Domino Server. It’s hard to find information about NSF storage which makes hard to implement the data transferring from NSF storage.

The main risk that you should remember is that migration can’t be accurate for 100% between platforms. Files, attachments, data, settings, history, text layout can be corrupted or lost.

How to deal with NSF storage?

Aspose.Email takes care of it. The API has versions for .NET, Java and others, implementing methods to work with NSF storage. Therefore, you don’t need to spend time and resources to implement them by yourself.

Aspose.Email provides NotesStorageFacility class with EnumerateMessages method to read NSF storage files. It iterates over the messages in the NSF storage file. The following sample code demonstrates how to use is for reading messages from the NSF storage file.

// For complete examples and data files, please go to https://github.com/aspose-email/Aspose.Email-for-.NET
// The path to the File directory.
string dataDir = RunExamples.GetDataDir_Email();
using (NotesStorageFacility nsf = new NotesStorageFacility(dataDir + "SampleNSF.nsf"))
{
    foreach (MailMessage eml in nsf.EnumerateMessages())
    {
        eml.Save(eml.Subject + ".eml", SaveOptions.DefaultEml);
    }
}

Similar Java-based example:

// For complete examples and data files, please go to https://github.com/aspose-email/Aspose.Email-for-Java
// The path to the resource directory.
String dataDir = Utils.getSharedDataDir(ReadMessagesFromNSFStorage.class) + "email/";
NotesStorageFacility nsf = new NotesStorageFacility(dataDir + "SampleNSF.nsf");
try {
for (MailMessage eml : nsf.enumerateMessages()) {
     eml.Save(eml.Subject + ".eml", SaveOptions.DefaultEml);
     }
} finally {
     nsf.dispose();
}

To find more about usage of Aspose.Email you can vist Working with IBM Notes.

You can say: "Ok. But how can I move my messages from NSF to PST?"
And this is a popular question.
Don't worry! Here is a sample of how simple it can be with Aspose.Email.
This library allows to work not only with NSF and PST formats but also with MSG, OST, OFT, EML, EMLX, MBOX, ICS, VCF, HTML, MHTML.

// For complete examples and data files, please go to https://github.com/aspose-email/Aspose.Email-for-.NET
//Initialize NSF storage
using (NotesStorageFacility nsf = new NotesStorageFacility("SampleNSF.nsf"))
{
    //Initialize PST storage
    using (PersonalStorage pst = PersonalStorage.Create("outputPST.pst", FileFormatVersion.Unicode))
    {
        //Creating 'Inbox' folder in PST storage
        FolderInfo pstFolder = pst.CreatePredefinedFolder("Inbox", StandardIpmFolder.Inbox);

         //Run throught NSF storage
         foreach (MailMessage eml in nsf.EnumerateMessages())
         {
             MapiMessage msg = MapiMessage.FromMailMessage(eml);

             //Adding message into the folder in PST storage
             pstFolder.AddMessage(msg);
          }
     }
}

There are many other features included in Aspose.Email API. Here you can find out more details!
When time allows, you can check out API examples at Github.
If you have any questions and other API related issues, ask in our forum.

Email client for MAC. Which one?

Artemiy Gazizyanov — Wed, 13 Nov 2019 11:15:59 +0000

There are many email clients for macOS.

I am a MAC user, and this is a really important topic for me personally and for my research in this area.

How did you choose email client for MAC from the variety of them?
Why did you choose your email client?

Please share your thoughts with me. Comment below!👇

Do you still use IBM Lotus Notes/Domino?

Artemiy Gazizyanov — Wed, 13 Nov 2019 08:15:16 +0000

I`m writing an article for Aspose.Email about the increasing amount of migrations from Lotus Notes/Domino.
Have you ever used it before?
Have you ever migrated from Lotus Notes/Domino to other services like SharePoint, etc.?

Please share your thoughts in the comments below! 👇👇👇

Outlook for Mac. How to convert OLM to PST?

Artemiy Gazizyanov — Thu, 31 Oct 2019 10:50:33 +0000

Necessity

On the one hand, we have Mac OS as the second most popular operating system. On the other hand, we have Outlook as one of the most popular personal information managers in the world. So, it was a question of time when we were able to use all functions of Outlook on Mac.

Now we have Outlook for Mac OS provided by Microsoft Office. This application is a full-weight version of Outlook for Windows, but we can use it on Mac OS. There is only one difference. It is a storage file format. The version for Mac OS uses OML against PST on Windows.

So one of the most prevalent problems to solve is converting from OML files to PST. That can be done for many reasons: to send data on a Windows machine for some processing or to save data according to the saving data.

Save and protect your data

One of the cases that users of Mac OS encounter are errors that occur when saving data and their further damage.
It can be caused by compatibility between MAC OS and Outlook for Mac. When these two applications don’t synchronize as well. Then Outlook can give various error messages or exceptions like:
“Microsoft Outlook must be closed because an error occurred. Any unsaved work may be lost.”
“Sync pending for this folder”
“attachments exceed the limit allowed please remove attachments, sync error code 17193”🤦‍♂️

Do you save your outlook data and how do you do it?
Share your comments below! 👇👇👇

You can go two ways:
1. You can try to fix them to handle the compatibility issues doing: continuous updating to the latest updates or to export all the Outlook data in the OLM files using the Export option.
2. Use Aspose.Email library to convert OML files to PST to save data to protect it or transfer.

Usage

string dst = "SampleOLM.olm";

//Initialize Olm storage
using (OlmStorage storage = new OlmStorage(dst))
{
    //Initialize Pst storage
    using (PersonalStorage pst = PersonalStorage.Create("output.pst", FileFormatVersion.Unicode))
    {
        //Create only Inbox folder as an example
        FolderInfo pstFolder = pst.CreatePredefinedFolder("Inbox", StandardIpmFolder.Inbox);

        //Go through folders in the OLM storage
        foreach (OlmFolder folder in storage.FolderHierarchy)
        {
            //Check is this folder empty
            if (folder.HasMessages)
            {
                 // extract messages from folder
                 foreach (MapiMessage msg in storage.EnumerateMessages(folder))
                 {
                     //Add message to the pst storage
                     pstFolder.AddMessage(msg);
                     Console.WriteLine("Subject: " + msg.Subject);
                 }
            }
        }
    }
}

This approach is secure because you don’t have to send your data to a third-party server; all processes take place on your machine.
This library saves the integrity of the whole OLM file. Also, PST has a split feature that can allow users to divide a large PST file into smaller-sized PST files.

After successful converting, the PST file can be saved on your machine or can be migrated to the Outlook for Windows or to the other applications which can support this file.

Do you often face similar problems and how do you solve them?
Leave your comments below. 👇👇👇