DEV Community: aashiya123

How to Build a Data Science Portfolio

aashiya123 — Thu, 23 Jun 2022 16:37:04 +0000

Earlier, recruitments were based on the technical knowledge that we mentioned in the CV or resume. Today organizations demand more industry-relevant hands-on experience over theoretical knowledge. Employers look for the work the candidate has done in that particular field. Thus an overall portfolio will help in setting a benchmark for selecting the candidates. Well, this is not required for every IT field, but if we consider the Data Science industry, then having a portfolio is essential as the employers will decide based on your work and the practical knowledge you have.

Having a Data Science portfolio will help you showcase the skills that will allow you to stand out among other candidates appearing for the same job. If you have done your homework correctly, it will help you get the dream job you desired—all you have to do is showcase your data science on the portfolio. Without much ado, let’s understand the importance of having a data science portfolio to land a top gig as a data analyst, data scientist, or any other data-related job role.

What is a Data Science portfolio?
Like any other professional portfolio, a data science portfolio helps candidate showcase their talent and skills through their projects. Having a solid portfolio will highlight your ability to solve research questions, analyze data, gather project insights, how well you can collaborate with other team members, and your ability to communicate your findings to the users. All this is possible only if you have a solid technical background.

Having a data science portfolio will help establish trust with your hiring manager so he will be sure that you are the desired candidate for the job. Also, you do not have to worry if you are a beginner in the industry and do not possess any experience in any technical field. An attractive data science portfolio will divert the recruiter’s attention more towards your portfolio to judge your skills.

Creating a portfolio for data science is easy for beginners as it offers various public datasets that they can use in their projects. If you have creativity, you can even accommodate every feature using the public dataset rather than spending on the project.

Why is there a need to have a data science portfolio?
Well, most employers look for the degree and technical skills that you possess. They majorly focus on where you got your degree from. If it is a prestigious college or institute, they will be confident that the candidate must have the right skill set that is required for the data science job. But if you do not have a proper degree in data science, you have the lowest chance of getting the job. But if you have a data science portfolio showcasing your creativity, talent, and technical skills, you will be considered for the job. Being a data scientist will require strong technical knowledge and how to use various tools for working with data.

Thus, it is important that you carry your data science portfolio to get the dream job you thought of. If you are new to data science and do not have any idea how you can start working on your data science portfolio then you can go through the below-mentioned tips for creating one and get noticed during interviews.
Tips to Create a Data Science Portfolio

Create a GitHub Profile
With GitHub, you will be able to host the remote version of your data science project to be visible to everyone. Make sure you have an active GitHub profile so that you can add a link to your CV. an active profile refers that you are working on it regularly to make adequate changes and are visible to your viewers. It is a good practice to have a readme.md for your profile for customizing your homepage.
Make proper use of Kaggle
If you want to practice and showcase your skills on a regular basis, then it is recommended to have a Kaggle account. This site is popular among several big companies and used for carrying out competitions for hiring suitable Data science candidates. Kaggle also helps in understanding the techniques and tips that you can use while working with data. You can go through its tests and earn medals that will be beneficial for you and add a plus point during the interview. Also, you can add the link for your Kaggle account on your CV. below is an example of the Kaggle profile.
Participate in various Competitions and Hackathons
If you want to test your technical knowledge in data science then you can appear for various online competitions and hackathons. It will help you to know where you stand and your position among the peer groups. You can even add your achievements in your CV along with a link to your online certificate for that competition. There are various online platforms where you can appear for the exam and test your skills.
Prepare yourself using HackerRank
For becoming a data scientist, you need to have various technical skills and strong knowledge of programming languages like Python. You can prepare yourself by engaging yourself in various platforms for enhancing your skills. You can solve and practice questions available on the HackerRank website and add your achievements to your CV for being a better candidate for the profile.

*Some examples for the Data science portfolio *
The main purpose of having a Data Scientist portfolio is to showcase your technical skills and convince the hiring manager that you are the right candidate for the job. So make sure, you add the case studies to your profile. We have mentioned some of the project types that you can create and mention in your CV.

Data cleaning projects
One of the key roles of a data scientist is to clean and arrange the messy data of any company. So it is a better idea to add a project that involves data cleaning. Make sure to use existing messy data sets, then try to explore data to clean it up and perform analysis to get better insights. This will create a strong base for you to get selected.
Data Storytelling Project
Due to the expansion in data for any company, there is a huge amount of raw data that is not arranged and does not make any sense. Being a data scientist, it is your job to find the correlation in the existing data and to fit them into a story narration so they make some sense. You can add an example where you have implemented this approach.
Machine Learning Project
If you include a machine learning project, it will help in specifying your progress in the required technical knowledge. Creating a machine learning project will require knowledge of algorithms that will work on the entered data and create an output. You can showcase your understanding of the algorithms that is a plus point for the hiring manager and put you in the technical role.

Conclusion
Data scientists are in great demand and require a unique and strong skill set to become one. Having the right knowledge is not enough to get selected if you do not know how to implement that knowledge in a project. So instead of having theoretical knowledge, you must focus on practical one as recruiters focus on how a candidate is able to apply that knowledge. So having a portfolio will help both the candidate and the recruiter. Candidates will be able to showcase their talents and the recruiter will get a base for selecting the candidate based on the candidate’s talent. So make sure to create a Data scientist portfolio for better job opportunities.

How to update PHP in WordPress?

aashiya123 — Mon, 03 Jan 2022 06:08:18 +0000

If you own your web server, you can make changes yourself, but if you have hosted your website via a third-party then you need to contact them for making the required PHP changes. But having a third-party, it will not be your job to manage and maintain the updates, they will do it on their own whenever a new version update is available. Same goes with the plugins, themes, and PHP version.

Via cPanel
It also follows the same steps as login into your web hosting account. Then you can look for the software section where you can check the selected PHP version as shown below.

Click it and you can see the next page displaying the PHP version. From there, you can select the latest version for the PHP as shown below.

Via WordPress

You can follow the below-mentioned simple steps to check the PHP version.
You can look for the plugin “Display PHP Version” and install it. You can find it in the WordPress repository as shown below.

You can now activate the plugin. Then navigate to the WordPress dashboard-> home-> at a glance.
You will be redirected to the new page where you will be able to see the PHP version on which your website is running.

click the Update option available.

Contacting host provider
If you are using a third-party for hosting your website, then you need to contact them for making the required changes. These host providers have skilled persons for making such changes either via code or via interface depending on the changes.

HELM Cheatsheet: For Beginners

aashiya123 — Fri, 31 Dec 2021 06:01:25 +0000

The Helm is a package and operation manager for Kubernetes. Though handling Kubernetes applications and several releases can increase the development and deployment complexities. The Helm as a packaging manager allows you to wrap up all the Kubernetes components within a single package for deployment, thus reducing complexities. You can integrate several Kubernetes objects within the Helm chart, which is deployed as a whole. You can use Helm to deploy a single application or a part of an extensive application.

There are a number of tools that can be used with Helm charts to ease the Kubernetes deployment process. You can also integrate the Helm charts within the CI/CD process to automate each process, giving developers leverage to work on writing codes rather than running and handling production deployments. You can use and install the Helm with one click. Helm comes with the command-line user interface called ‘helm’ to perform the Helm functionalities.

Below are some Helm commands

helm help command

The above command will provide you information about the available Helm commands.

# helm help

If you want any details about the Helm command, you can use the helm help below.

# helm help search

helm search command

The above command will allow you to search for the charts. You can use helm search as mentioned below.

# helm search phpmyadmin

output-
NAME CHART VERSION APP VERSION DESCRIPTION
stable/phpmyadmin 4.3.5 5.0.1 DEPRECATED phpMyAdmin is an mysql administration frontend

helm fetch command

With the above command, you can download the chart locally without installing it. You can use the chart name with the fetch command to download all the charts and template files within the directory.

# helm fetch stable/phpmyadmin
# ls -ltr

output-
Total 32
-rw-r--r-- 1 root root 28921 Jun 29 11:04 phpmyadmin-4.3.5.tgz

helm install command

Using the above command, you can easily install the chart followed by the chart name. You can use the ‘- name’ option if you want to name the deploy chart and ‘- version’ to specify the chart version as per your requirement.

# helm install stable/phpmyadmin --name myphpadmin --version 4.3.3

The above command will provide the deployed resources overview, which can be checked from the Kubernetes with the below command.

# kubectl get all |grep -i myphpadmin

helm init command

You can use the above command to initialize the helm.

helm status command

You can check the chart installation status using the above command. You have to provide the chart name about which you want the status.

# helm status myphpadmin

helm list command

You can use the list command with complete details of the currently deployed chart.

# helm list

output-
NAME REVISION UPDATED STATUS CHART APP VERSION NAMESPACE
myphpadmin 1 Mon Jun 29 11:35:32 2020 DEPLOYED phpmyadmin-4.3.3 5.0.1 default

helm upgrade command

With the help of the upgrade command, you can upgrade the chart version. In the above examples, we have version 4.3.3, and now we are upgrading it to 4.3.4 using the below command.

# helm upgrade myphpadmin stable/phpmyadmin --version 4.3.4

helm history command

With the above command’s help, you can check the installed chart’s history followed by the chart name.

# helm history myphpadmin

output-

REVISION UPDATED STATUS CHART APP VERSION DESCRIPTION
1 Mon Jun 29 11:35:32 2020 SUPERSEDED phpmyadmin-4.3.3 5.0.1 Install complete
2 Mon Jun 29 11:53:48 2020 DEPLOYED phpmyadmin-4.3.4 5.0.1 Upgrade complete

helm rollback command

You can use the rollback command if you want to move to the previous version of the helm chart. You have to mention the version number with the command as mentioned below.

# helm rollback myphpadmin 1
Rollback was a success.

helm delete command

You can delete the helm chart using the delete command as mentioned below.

# helm delete myphpadmin
release "myphpadmin" deleted

helm repo list command

With the help of the above command, you can list down the repositories used currently.

# helm repo list

output-
NAME URL
stable https://kubernetes-charts.storage.googleapis.com
local http://127.0.0.1:8879/charts

helm repo update command With the help of the above command, you can update the repositories.

# helm repo update

output-
Hang tight while we grab the latest from your chart repositories...
...Skip local chart repository
...Successfully got an update from the "stable" chart repository
Update Complete.

helm reset command

You can use the reset command to uninstall the tiller component and the ‘-remove-helm-home’ option after the remove command to remove the helm’s home directory. You can use the ‘-f’ option to remove it forcefully.

# helm reset -f --remove-helm-home

output-
Deleting /root/.helm
Tiller (the Helm server-side component) has been uninstalled from your Kubernetes Cluster.

Chart installation and manipulation command

Creating chart template The above command will allow you to create the chart template with the .

# helm create

overriding helm values
helm install --name --values config.yaml --timeout 300 --wait stable/mysql
Setting environment variable on creating release
helm install --set x=somevalue -f config.yaml --name
To check the syntax of the helm chart
helm lint
helm lint
To upgrade the chart or variables in a release
helm upgrade --values config.yaml
To inspect the chart details along with the chart name.
helm inspect
To inspect the values assigned in the chart along with the chart name.
helm inspect values
To create package as a .tgz file [if you have chartmuseum]
_helm package _
_helm package . _
To install chart dependencies
helm dep up _
_helm dependency update

Git Commands Cheatsheet: Beginners (18-20+ basic Git Commands)

aashiya123 — Tue, 28 Dec 2021 05:41:38 +0000

Git is a free and open-source distributed version control system that handles every change within the project. Git software runs on the local machine to keep track of the files and their history. You can also use Git’s online hosts to store files. It also allows you to have a centralized place to store files to ensure easy access. With Git, you can easily make parallel changes that can be merged later without any issue.

Features of Git

It allows you to track history.
It is a free and open-source distributed version control system.
It supports non-linear development.
It allows you to create backups.
You can scale it according to your business needs.
It enhances team collaboration.
It ensures easy branching.
It supports distributed development.

*Git workflow *

Git workflow has three different stages-
Working directory- it allows you to alter the files and codes within your working directory.
Staging area- it allows you to stage the files and add their snapshots to the staging area.
Git directory or repository- it allows you to commit the modification permanently.

Basic Git commands
Creating a repository

Creating a new local repository from scratch
$ git init [project name]
Downloading from an existing repository
$ git clone my_url

Observing your repository

Listing new or modified files that are not being committed yet.
$ git status
Displaying the file changes that are not being staged
$ git diff
Display the change to the staged files
$ git diff --cached
Display all the staged and unstaged file changes
$ git diff HEAD
Display the differences between two commit ids
$ git diff commit1 commit2
Listing the dates and the author of the changed file
$ git blame [file]
Display the file changes for a particular id or a file
$ git show [commit]:[file]
Display the complete change history
$ git log
It will display the change history for a particular file or a directory
$ git log -p [file/directory]

Working with branches

It will display all the local branches
$ git branch
It will display all the local as well as the remote branches
$ git branch -av
It will switch to a branch and will update the working directory accordingly
$ git checkout my_branch
It will create a new branch named new_branch
$ git branch new_branch
It will delete the branch named my_branch
$ git branch -d my_branch
It will merge two branches, branch_a, and branch_b
$ git checkout branch_b
$ git merge branch_a
It will tag the current commit.
$ git tag my_tag

Making changes

To stage the file and ready to commit
$ git add [file]
It will stage all the changed file and ready to commit
$ git add .
It will commit all the staged files to the versioned history
$ git commit -m “commit message”
It will commit all the tracked file to the versioned history
$ git commit -am “commit message”
It will unstage the file and keep the file changes
$ git reset [file]
It will revert everything to the last commit
$ git reset --hard

Synchronize

It will get the latest changes from the origin
$ git fetch
It will fetch the latest changes from the origin and merge
$ git pull
It will fetch the latest changes from the origin and rebase
$ git pull --rebase
It will push the local changes to the origin
$ git push

Help command

Use the git help command for more details $ git command --help

DevOps Myths! Are these true?

aashiya123 — Mon, 27 Dec 2021 09:56:50 +0000

Irrespective of many DevOps myths around the market, it is still deployed to achieve effective decision making. DevOps definition may vary from company to company, thus results in a different way of implementation. DevOps tends to improve the speed and quality of the software delivery process with agile technology, but it may not work in the same way. DevOps results are significant when it is appropriately implemented and can improve the working within the organization.

But before we implement it, we need to understand what it means to the organization and how we want it to impact our work. So we have to consider and understand the myths that are revolving around the market. We have discussed a few of them in detail.

Myth 1- DevOps is a replacement for Agile.
It is not entirely true that DevOps is a replacement, but it is more a successor to Agile that has overcome some of the hindrances using Agile. With time, Agile has been evolved and grown with some of the challenges, which later on optimized with DevOps. Agile lacks communications among different team members working on various project stages resolved by DevOps and saves the team morale without any blame game. Unlike Agile, a DevOps service engineer will perform activities from developing to deploying code into production.

Myth 2- DevOps implementation may vary from project to project
Though every project has different requirements and demands from the coding, testing, and deployment perspective, so DevOps practice must be flexible so that every team can adapt accordingly. If you have the proper understanding of the DevOps procedure, only you will be able to implement it efficiently based on different project needs. But the working process will be the same if you are implementing DevOps as the procedure are standard.

Myth 3- DevOps deals with automated tools
DevOps is an approach that provides you with a different way to deploy and manage your applications and project. DevOps comes with many practices like collaboration, CI/CD, and continuous testing, which need to be understood for implementation. Well, the DevOps procedure can be implemented using various tools like JIRA, Git Hub, Chef, Puppet, and many more. But you will be able to perform the DevOps process efficiently when you know how to leverage and optimize these tools. So, DevOps is all about methodology and standard procedures that need to be followed irrespective of the provided toolset.

Myth 4- Error rates tend to raise using DevOps
Well, DevOps is an approach where you follow procedures to get immediate feedback about your application code. This will intend to discover more errors than before to make the application completely error-free. This will, in turn, log several mistakes than before, which is obvious. Many organizations feel using DevOps raising the level of accounted errors without even realizing that the mistakes have always been there. Still, with the DevOps approach, errors are now coming up to the surface more clearly. In this way, you will get the learning and a way to remove all possible errors.

Myth 5- Automation will overcome all hindrances.
DevOps offers you benefits like automating the deployment process, but it will not completely solve all the problems. Automating the continuous integration and deployment process will be efficient to some extent as it is applicable for one or two stages of the software delivery process. DevOps process requires team collaboration; otherwise, automating the process at one stage will move all the bottlenecks to another stage.

Myth 6- DevOps means NoOps
It is a myth that DevOps has nothing to do with IT operations. It is because mostly DevOps is more dedicated to deploy codes and maintain service levels. But, we cannot say that the development part is overpowering IT operational services. If we want to leverage DevOps completely to get instant feedback, speed, and quality, IT operations have a significant role in implementing it. There is also a great dependency of DevOps on IT services to get the work done in lead time.

Myth 7- DevOps is not suitable for large and complex systems.
Working with a complex system requires team collaboration on a large scale to get the work done efficiently. DevOps comes with the benefit of collaborating, integrating, and integration features, making it suitable for large projects. However, the complex system has various demands of software and hardware pertaining to different delivery cycles, which is also handled by DevOps with excellent coordination.

Git Commands Cheatsheet: Advanced (20+ Git Commands Advanced )

aashiya123 — Mon, 27 Dec 2021 06:19:49 +0000

If you are working on a project, whether small or large-scale, you need to track every change made within your team space. You can use any software or applications to keep that track, but we will discuss what Git is, how it works, and some advanced Git commands.

What is Git?
Git is an open-source Version Control System that allows you to work within teams in a unique way. You can use a number of commands and functions to work on the project and keep track of the code changes. It will manage all the changed versions of files and directories. As the project expands, the number of tests increases results in changing code with a version number that can be recovered later. It allows the developers and other project members to keep track of- what changes are made, who made those changes, when the changes were made, and why those changes were required.

Git is a distributed version control system commonly used for commercial software development and complete access to every file, directory, and iteration of the project. With Git, you do not have to be connected to the central repository due to which developers can collaborate with the team from anywhere. The main advantage of using Git is its branching capabilities, which are easy to merge.

Working of Git
Git stores everything like files and directories in binary large object forms, which are represented as trees. These trees can contain other trees or large objects along with text files containing information about those files. If a repository transfer contains many files with the same name but different content, it will also get transferred as large objects, which later get expanded to separate files.

Commit object contains the project’s complete history; any change to the project has to be committed. This commit object file will contain the information about that change.

Git Advanced commands

How to configure the tooling commands
The below command will set the name of your commit transactions.
$ git config –global user.name “[name]”
The below command will set the email to your commit transactions.
$ git config –global user.email “[email address]”
How to create Repositories
The below command will create a new repository with a specified name.
$ git init [project-name]
The below command will allow you to download a project and its complete version.
$ git clone [url]
How to refactor the file name
The below command will delete the file from the working directory and stages the deletion.
$ git rm [file]
The below command will allow you to delta the file from the version control but saves it locally.
$ $ git rm –cached [file]
The below command will change the file name and prepare it for commit.
$ git mv [file-original] [file-renamed]
How to suppress the tracking
The below command will list all the ignored files within the project.
$ git ls-files –others –ignored –exclude-standard
How to shelve and restore incomplete changes
The below command will temporarily store all the modified tracked files.
$ git stash
The below command will restore the most recently stashed file.
$ git stash pop
The below command will list all the stashed changesets.
$ git stash list
The below command will discard the most recently stashed changeset.
$ git stash drop
Commands to erase mistakes
The below command will undo all the commits but preserve the changes locally.
$ git reset [commit]
The below command will discard all the history and changes back to the specific commit.
$ git reset –hard [commit]
Commands for group changes
The below command will display all the local branches in the current repository.
$ git branch
The below command will allow you to create a new branch.
$ git branch [branch-name]
The below command will delete the specified branch.
$ git branch -d [branch-name]
Miscellaneous commands
The below command will allow you to connect your local repository to the remote server.
$ git remote add [variable name] [Remote Server Link]

To Split a subfolder out in a new repository.
$ git filter-branch --prune-empty --subdirectory-filter master
To remove untracked files
$ git clean -f

To remove untracked files/directories
$ git clean -fd

list all files/directories that would be removed
$ git clean -nfd

The below command will tar the project files without .git directory.
$ tar cJf .tar.xz / --exclude-vcs

Why should you learn Kotlin in 2022?

aashiya123 — Fri, 24 Dec 2021 07:57:44 +0000

We all know about the fact that Java is being considered to be the best possible language for Android application development until Kotlin comes into the light. With all the flaws, Java was used and is being mostly used by developers and companies to build Android apps. But after Google announced Kotlin as an official language for Android development which has overcome the flaws in Java, Kotlin has become the highly preferred platform for development. It is now high time that you switch to Kotlin and leave Java behind for good.

Many companies like Pinterest, Netflix, and many others have embraced the Kotlin. If you start working with Kotlin, you will get a good amount of tools and frameworks that can be easily integrated with Java.

What is Kotlin?
Kotlin is developed by JetBrains and named after the Kotlin island near St. Petersburg, Russia. It is a cross-platform, general programming, statically typed, and open-source programming language that can be run on Java virtual machines. It is an alternative to Java but the Kotlin’s syntax is not compatible with Java but it can interoperate with Java. it allows you to run Kotlin’s code with Java and individually. Kotlin comes with an aggressive interface that allows you to determine the values and expression types if they are not declared which makes it different from Java.

Kotlin has gained popularity after it is being supported by Google and is adopted as a first-class Android development language. Kotlin has many useful features and is expressive which makes it a great alternative for Java. JetBrains has made the language fault-proof which is easier to maintain. Kotlin can also be used for JVM development using Java frameworks. Also, JetBrains is working on the Kotlin multi-platform that will allow you to develop multi-platform applications with shared codebases.

Features of Kotlin
Below are the common and attractive features of Kotlin.

It is based on the Java environment and platform so you can run Kotlin’s code easily on any Java platform.
It has easy and familiar syntax and programming structure which makes Kotlin a great option to modify and identify errors.
It comes with an advanced compiler that can track automatic casts which will improve the efficiency of the check timings.
Kotlin comes with easy symbols that can be understood easily without any special arguments.
You can easily execute data in a class with a simple line like toString(), equals(0, etc.
It has an easy set-up process, all you need is a Kotlin plugin for your Android studio.

Advantages of using Kotlin
In a lesser time, Kotlin has become an efficient programming language that is considered to be an alternative to the most commonly used robust Java language. It has various advantages as mentioned-below-

It helps in increasing team efficiency because of its intuitive syntax. With Kotlin you can write code in a few lines and less time.
Kotlin’s code can be easily compiled with the existing Java code as Kotlin is Java-interoperable and is consistent with all Java tools and frameworks.
Kotlin comes with the great support of various IDEs and SDK tools which allows developers to work with their choice of platform and toolkit.
Kotlin has a compact codebase that makes it a stable and consistent language for code development. You can easily detect codes at compile-time which can be resolved before running the code.

Disadvantages of using Kotlin
Despite all of the above-mentioned advantages, Kotlin also has some disadvantages. So make sure that you want to implement it in your system irrespective of all downfalls.

It is said that both Java and Kotlin have similarities when it comes to code structure and basic syntax but in the end, both are different. Kotlin cannot be completely considered as Java. to implement it into your system you have team expertise in Kotlin and requires Kotlin training.
In some cases, Kotlin works faster but when it comes to clean builds Java is still superior to Kotlin.
As it is new to the market, there is less number of experts available in the market for Kotlin.

Reasons to adopt Kotlin

Kotlin comes with a mature environment, it has gone through many stages before its first release thus making it bugs free to much extent. Its IDE plugins work effortlessly. It has been used in many projects in its alpha and beta phase.
Kotlin overcomes many pitfalls of Java thus making it a powerful programming language along with simplicity. Kotlin’s compilation time is very less as compared to other alternatives and Kotlin apps require less library.
Kotlin helps in reducing the bugs level by integrating its safety features within your apps. It ensures that variables used cannot be null and can be identified at the compile time before moving it to production.
If you belong to a Java background then you can get started with Kotlin easily. Also, you can get many resources to learn the basic syntax and advanced topics. It is a better option for both beginners as well as experienced developers as it improves productivity by making debugging easier.
The use of Kotlin is not only limited to Android apps. As it is JVM based so can be run easily on every platform that supports JVM. Kotlin allows you to do front-end development also.