teleren/devto huggingface dataset:
The Space App - a help for post Corona era
Tags: octograd2020, githubsdp, android, github
Published: 2020-05-20 10:10:27

The Space App is an Android application which helps people practice social-distancing. This app was designed keeping post Corona era in mind.The app uses the Google Maps API to determine distance between two users and Google Firebase to read and write data their distance, latitude, longitude, and status from cloud. With the help of multi-threading the app refresh itself automatically every 2 minutes. This app helps user keep an eye on the head count within user's 1.5m radius and a haptic feedback is generated if the limit exceeds giving users instant feedback. 


## Demo Link
 https://drive.google.com/file/d/1jWKkFHVG9c2p9AGbhVlyeZ-9oIbMBsVm/view 

## Link to Code
https://github.com/iamHrithikRaj/TheSpaceApp

## How I built it 
I made this app during my quarantine time and I learned a lot.
I started off with creating a basic layout for my app. Then integrated the Google's Firebase.After creating the login/registration for the users I integrated the Google's Map API. Now there was i serious problem i ran into,the Map API was not that accurate for very small distances therefore the number of people in users 1.5m radius was not that accurate.
Searching online i found out that Distance Matrix API is suitable for such cases.
So maybe I'll try integrating Distance Matrix API as well.
This was my first major Android project. 
During this time i was more productive than ever before, I was done with my project in 96hrs, just because ofPomoDone. I got PomoDone lite plan free for 2-years from GitHub Student Developer Pack #githubsdp.
With PomoDone, I tracked my time and boosted my productivity by applying Pomodoro technique to my workflow.
I always wanted to help the society using my knowledge and this was the first time i made it happen.So I'm really proud of myself.

###Final Note:
The app is still in its alpha version and I'm working on it. I would love to know any feedback and collaborate with other amazing developers to take this project forward.
Scholarships Info for Physically Challenged Students
Tags: devgrad2020, octograd2020
Published: 2020-05-20 10:09:39

Hi there! Here, I'm going to talk about one of my favorite projects till date. I have worked on various projects and on various topics so far. But this one is always special for me, maybe because it serves a cause. The idea is to provide scholarship details for physically challenged students. Not having any scholarship opportunity is different and not utilizing an opportunity is different. So, I have come up with this app so that all the students have an opportunity to study.

The new features are yet to be added to this app, say extending voice support. So, it is basically under pause. Here is the link to the [code](https://github.com/PratyushaThumiki/HelpOrg). There's a lot to be done to this app, the data to be added is huge and only Indian Government API has been taken for it's working. Will improve the app and publish it after completion.
Thank you for taking your time to read this.
One License - Degree Project [WIP]
Tags: octograd2020, githubsdp
Published: 2020-05-20 10:08:44



[Comment]: # (All of this is placeholder text. Use this format or any other format of your choosing to best describe your project and experience.)

[Note]: # (If you used the GitHub Student Developer Pack on your project, add the "#githubsdp" tag above. We’d also love to know which services you used and how you used it!)

## My Final Project
For my degree final project I was assigned to make a generic licensing solution for offline software deliveries. I've name this project `One License` as it is meant to be generic. 

It is a module for a broader project which deals with auto deployment of machine learning models and makes APIs available in a marketplace. 

The One Licensing solution allows you to license your offline softwares which can be either time bound or limited to number of API calls. It also has some fraud prevention mechanism but I won't say they are completely hack proof(duh!), instead it just more difficult/inefficient for the users to hack it. 

One License Thin Client is software that prevent license misuse using different strategies. One of the ways to do fraud is running the licensed software on VM Clones. One License Thin Client prevents this by detecting VMs. The softwares are allowed to be used inside the VMs but the license validation request is first made to the Thin Client which runs on a real machine and this further makes call to the licensing server. 

## Demo Link
 
This project is still a work in progress the docs are not ready but you can still check it out.

[https://one-license-dashboard.herokuapp.com/](https://one-license-dashboard.herokuapp.com/)

## Link to Code

1. [Licensing server](https://github.com/one-ai/one-license-server)
2. [Dashboard](https://github.com/one-ai/one-license-dashboard)
3. Thin client (Work in progress)
4. [Integration libraries](https://github.com/one-ai/one-license-client)

[Note]: # (Our markdown editor supports pretty embeds. If you're sharing a GitHub repo, try this syntax: `{% github link_to_your_repo %}`)

## How I built it (what's the stack? did I run into issues or discover something new along the way?)

- I built the server using NodeJS + TypeScript.
- Used ReactJS + TypeScript for the dashboard
- Used Python for the client library since it was an immediate requirement. Clients in more languages will come soon. 
- For the thin client I'm planning Electron with obfuscation and binarization. 

Well the most difficult part was the fraud prevention step. I brainstormed on various cases with a hacker mindset and then wrote cases for prevention. Since it is meant to be run on the client system, I can only make it difficult for the client to hack the software. 


[Final Note]: # (CONGRATULATIONS!!! You are amazing!)
Chatbot as Digital Assistant
Tags: octograd2020
Published: 2020-05-20 10:08:29

## Introduction
Hi, my name is Mahan and I'm a Computer Science graduate for the class of 2020. I am currently working as a Senior Full-Stack Developer focusing on web development with Node.js. 

## My Final Project
For my Final Year Project, I created a chatbot for the faculty of my university. This chatbot aims to help faculty with their everyday tasks by simplifying the process. 

The focus of my project was using chatbots as digital assistants so because of this my thesis includes a lot of theoretical work explaining all the details of how chatbots work and what is required of them to be classed as a digital assistant.

The practical aspect of my project was split into four main sections;
1. Creating and training the chatbot using Google's [Dialogflow](https://dialogflow.com)
2. Creating an application layer that will be used to provide personalized information to the bot when needed. This application was created with [Golang](https://golang.org/) and was placed in between Dialogflow and the database
3. Implementing the chatbot into the current university system (UNIC Portal) which is based on Node.js
4. Adding an administrative panel for system administrators to be able to manage and monitor the chatbot. (On the same system as previous point)

## More in-depth explanation of the above sections
### Creating and training the chatbot

### Application Layer Used for Personalizing the Chatbot

### Implementing Into the Current University System

### Admin Panel 


## Notes
This blog post is currently not complete. I am still in the process of finalizing my thesis for submission and presentation so I don't have a lot of free time but I will definitely come back and add many more details as soon as I can. The only reason I have published it is because I need a link for the Github Graduation application.

If anyone has any questions or is interested in this project, you can contact me, I'd love to speak about it!

Unfortunately, I cannot share the Github repo of my project since this is a software that is already live and being used and the source needs to stay private.
[Zrav Chatbot]
Tags: octograd2020
Published: 2020-05-20 10:04:53

[Comment]: # (All of this is placeholder text. Use this format or any other format of your choosing to best describe your project and experience.)

[Note]: # (If you used the GitHub Student Developer Pack on your project, add the "#githubsdp" tag above. We’d also love to know which services you used and how you used it!)

## My Final Project
Create a Chatbot web based using NodeJS.

## Demo Link
 https://hackathon-kmipn-2020.herokuapp.com/

## Link to Code
{% github https://github.com/alfaben12/hackathon-kmipn-2020 %}
[Note]: # (Our markdown editor supports pretty embeds. If you're sharing a GitHub repo, try this syntax: `{% github link_to_your_repo %}`)

## How I built it (what's the stack? did I run into issues or discover something new along the way?)

Create a dataset of questions and answers then train data plus classification with node-nlp. condition how many things if the answer is not found or the other (ex consisi: the value of the classification is less than 2 then the answer is considered to be absent)

Tech stack:
- NodeJS
- ExpressJS
- Jquery

The problem that I found when making this was an inaccurate classification and still looking for a strong classification with nodejs

## Additional Thoughts / Feelings / Stories
Every day is a new day, and you’ll never be able to find happiness if you don’t move on. lets create issue on my github repo!

[Final Note]: # (CONGRATULATIONS!!! You are amazing!)
Cancer-Detection
Tags: 2020devgrad, octograd2020, showdev, githubsdp
Published: 2020-05-20 10:02:46

---
title: Cancer-Detection
published: true
description: I just graduated from Laramie High School, and this was my final project for my STEM class.
tags: 2020devgrad, octograd2020, showdev, githubsdp
---

[Comment]: # "Cancer tumor malignancy rating using advanced machine learning techniques."

## Cancer-Detection

Machine learning aids in many of our day-to-day ordeals in normal life. Some of the most powerful uses of machine learning are in the medical field. In this repository, the viability of artificial neural networks and support vector machines in tumor malignancy classification is tested.

### Simplified Pipeline

Step 1: Data acquisition

-   A publically available UCI Wisconsin breast cancer dataset is downloaded. Within this dataset, features are computed from a digitized image of a fine needle aspirate (FNA) of a breast mass.

Step 2: Data visualization

-   To effectively identifiy relationships within the data itself, a heatmap of all 31 features within the data is created.

Step 3: Data pre-processing

-   Attributes are seperated according to the following specifications:

    -   The first attribute of each sample is an ID number and is discarded

    -   Y (attribute 31): This final attribute is the tumor classification, malignant and benign, represented numerically as either 1 or 0. This feature is separated from the rest of the data. This is referred to as the target feature.

    -   X (attributes 1 - 30): These remaining features are the predictors (mean radius, mean texture, mean perimeter, mean area, mean smoothness, etc.), which will be inputted into machine learning models

-   The data is also split into to sets, training and testing.

Step 4: Create and train an Artificial Neural Network.

-   Modern neural networks come in many shapes and sizes. For this project, a simple 5 layer neural network was chosen for it's decent performance with minimal computational overhead.

Step 6: Create and train a Support Vector Machine

-   The SVM model is explicitly searching for the best separating line between the two classes of data. This is done by first searching for the two closest overlapping samples and finding a line, typically linear, that connects them. The SVM then declares that the best separating line is the line that bisects  is perpendicular to  the connecting line.  This is repeated with many overlapping samples until the number of samples misclassified is minimized or, more generally, until  the  distance  between  the  separating  line  and  both  classes  of  data  is  maximized.

Step 7: Evaluate and visualize

-   Post Training, data from both data sets is stepped through both machine learning methods. This evaluation data is used generate the result plots.

### Results

Come see the results and more at my github repository. {% github https://github.com/jarulsamy/Cancer-Detection %}
Octograd2020 - Dissertation Project
Tags: octograd2020, githubsdp
Published: 2020-05-20 10:02:17

## My Final Project: Predicting stock price movements using news articles through implementing Deep Learning and NLP
My project involved building an end to end solution used to predict up/down price movements in the DJIA index price based on general news articles taken from American news sources over a one and a half year period. I completed my project in Python and used Keras to build my deep learning model. My programme was able to predict movements with over 70% accuracy.
5 Code Playgrounds To Test & Build Ideas On
Tags: javascript, html, css, code
Published: 2020-05-20 10:00:15

Over the past couple of years a variety of code playgrounds have emerged on the World Wide Web. Simply put, they allow you to build, test and preview FrontEnd code without the rigmarole of creating files, starting up your IDE or setting up a local server.

Listed below are 5 of the most popular code playgrounds used by developers everyday. They all offer different ways to experiment with client-side code, share our creations with others and include features such as:

+ HTML & CSS Pre-processing
+ Quick start using popular JavaScript frameworks
+ Hot Reloading
+ Intellisense & Autocomplete
+ Asset Hosting
+ Collaboration Mode
+ Keep editing while offline

---

## [CodeSandbox](https://codesandbox.io/)

>Web Development Made Faster
An instant IDE and prototyping tool for rapid web development.

## [Codepen](http://codepen.com/)

>CodePen is a social development environment for front-end designers and developers. Build and deploy a website, show off your work, build test cases to learn and debug, and find inspiration.

## [Glitch](https://glitch.com/)

>Build fast, full-stack web apps in your browser.

 
## [StackBlitz](https://stackblitz.com/)  
>Create, edit & deploy fullstack apps — in just one click.


## [JSFiddle](https://jsfiddle.net/) 
>Test your JavaScript, CSS, HTML or CoffeeScript online with JSFiddle code editor.

---
Do you already use these sites? Share your profiles below so we can all check out your awesome creations!
ALA GULI MANE
Tags: devgrad2020, octograd2020
Published: 2020-05-20 09:56:09

**MY PROJECT**

The project is an Android App for an ancient Traditional game of south India called "Ala Guli Mane" aka "MANCALA". Mancala game Android App Developed with AndroidStudio 1.0.2 To import just do Import Project To run the unit test create an AndroidTest configuration for the GameLibraryTestSuite class.
{% github https://github.com/Namrathalb/Mancala-App no-readme %}
**Additional Features:**

* most of the test where done on a Samsung Nexus S with Android 4.4.4 and a screen resolution of 800×480 never run the app in other real device, expected some problem with high resolution display.
* followed the Android Guidelines for the Layout, that's why for the back button was used the system one, that's available in all devices and that was intentionally left on the screen (in the new device it's not an HW button but it can be hidden by the app theme)
* animation is available only in the HvH game, still having some trouble with threading ad queue in the HvC game, because of the high speed of the events.
How To Create Helm Charts? Helm v2 vs Helm v3
Tags: helm, kubernetes, tiller, docker
Published: 2020-05-20 09:55:13

This video explains about Helm Charts and it's features. 
-What is Tiller?
-Diff between Helm v2 & Helm v3 
Check the link: https://youtu.be/e2bGLWef9gQ

{%youtube e2bGLWef9gQ%}
My First Android App - Kotlin and MVVM
Tags: octograd2020
Published: 2020-05-20 09:52:39

## Worldwide Corona Tracker
Given the current situation the world is in and what we are going through, the developer in me wanted to build something related to it. I mostly worked on this application on weekends and currently in the process to make it more professional looking so that I can publish it on playstore.

## Link to Code
The app is currently in development so it might undergo a lot of changes but if you are interested to contribute you can reach out to me. 
{% github github.com/ritwikshanker/GoCoronaGo no-readme %}


## How I built it 
So I have been interning at a Company this summer where I work as a Software Development Intern. So working on this personal project of mine was a big task for me as I had to manage company work and personal work, cooking, cleaning and god knows what all this lockdown has taught me to do. I had never worked on a full android app on my own and I dreamed of making this app open source one day so spaghetti code was not an option. I built this application using MVVM architecture with full code written in Kotlin and support from API Level 19 i.e. Android 4.4. It is still in very early stages so a lot of major changes have to be done but so far it has been a great learning experience. I have a lot of things in mind which I am currently working on and would love to hear new ideas and features to implement.


## Additional Thoughts 

Do check my repo and if you like my work don't forget to star the repo and you can always ping me if you are interested to contribute.
Bech Do!
Tags: octograd2020
Published: 2020-05-20 09:49:50

[Comment]: # (All of this is placeholder text. Use this format or any other format of your choosing to best describe your project and experience.)

[Note]: # (If you used the GitHub Student Developer Pack on your project, add the "#githubsdp" tag above. We’d also love to know which services you used and how you used it!)

## My Final Project
Here I present my **Simple Buying and Selling app** through which a person can upload picture of an item which he/she want to buy. Other users who want to purchase can simply see the contact no and the cost and can contact the owner. 

## Demo Link
 https://github.com/SAHARSH123/Buying_Selling_App

## Link to Code

[Note]: # (Our markdown editor supports pretty embeds. If you're sharing a GitHub repo, try this syntax: `{% github link_to_your_repo %}`)
https://github.com/SAHARSH123/Buying_Selling_App

## How I built it (what's the stack? did I run into issues or discover something new along the way?)
App is built using Java language,Firebase is used for back end purpose,Picasso dependencies were used for rendering images in real time.


## Additional Thoughts / Feelings / Stories
I have learnt a lot during this project. 


[Final Note]: # (CONGRATULATIONS!!! You are amazing!)
Deploy Spring Boot & MySQL on Kubernetes Explaining Volumes PV & PVC
Tags: springboot, persistentvolume, kubernetes, microservices
Published: 2020-05-20 09:47:16

The video shows how to build n deploy Spring Boot & MySQL Docker images to Kubernetes explaing about Persistent Volume(PV) & Persistent Volume Claim(PVC). Checkout the link: 
https://youtu.be/ThAkKPAwdpQ

{%youtube ThAkKPAwdpQ %}
Final project 🥳
Tags: octograd2020
Published: 2020-05-20 09:46:47

[Comment]: # (All of this is placeholder text. Use this format or any other format of your choosing to best describe your project and experience.)

[Note]: # (If you used the GitHub Student Developer Pack on your project, add the "#githubsdp" tag above. We’d also love to know which services you used and how you used it!)

## My Final Project
As part of my bachelor's degree project, we spend the final semester working on a project. We were a team of 3. We worked on developing an analytics platform specifically targeted at in-store shopping, by using wifi-enabled devices (Probe requests) and also by using cameras placed at the stores. We first pushed ourselves to get a POC and then got feedback on the same and got an MVP out before the final review.

## Demo Link

Our app is live but data on it depends on whether the hardware is set up at the facility or not. (Also we'd be experimenting on the same!)
[Shop Analytics](pisniff.tech)

## Link to Code

[Note]: # (Our markdown editor supports pretty embeds. If you're sharing a GitHub repo, try this syntax: `{% github link_to_your_repo %}`)
{% github Impeekay/shop-analytics-pi %}
{% github Impeekay/shop-analytics-backend %}
{% github Impeekay/shop-analytics-frontend %}

## How I built it (what's the stack? did I run into issues or discover something new along the way?)

- We used **Python** to write scripts for the Raspberry-pi.
- We enabled a connection between the devices via the **MQTT** Protocol which enables a lightweight data transfer between IoT devices.
- We used ***Tensorflow*** and also ***YOLO*** to enable the people detection which has several models which have the capability to run on embedded devices with low computing power. (I personally like YOLO!😅)
- We chose to use **Node.Js** for the backend because of the asynchronous, event-based actions that it enables us to work with.
- We used **react** for the frontend (cause why not!🚀) 
- Also, we used **ZMQ** for low-latency streaming of frames between the hardware and the backend server.
- Finally, we also used **Grafana** for the analytics part of it, where it was capable of querying and displaying graphs, and mostly because it has a lot of functionality as such.

## Additional Thoughts

We're actually proud of the work that we've done till now. There is also a lot more than can be done on the project(De-anonymization of MAC address). Also, we're shocked by the fact that we collected almost close to 20 Million Probe request packets in the span of 4 months. (Also, a lot of data to deal with TBH!😂).
Working on Object Lifetime Analysis for C++
Tags: octograd2020, clang, cpp, compilers
Published: 2020-05-20 09:38:54

## Lifetime Analysis

The end of my Ph.D. studies is approaching. It was quite a ride and I feel like I was able to contribute back a bit to the awesome community of C++. Object lifetimes are a common source of bugs in C++ that can cause crashes or other unexpected behavior. I had the chance to work with Herb Sutter, the chair of the ISO C++ Standard Committee. We defined and implemented multiple analyses that can help to catch common object lifetime problems.

This work was showcased in a CppCon 2018 [keynote](https://youtu.be/80BZxujhY38?t=1100) and Herb's [blog post](https://herbsutter.com/2018/09/20/lifetime-profile-v1-0-posted/).
We had some more talks about it at CppCon 2018, 2019 and EuroLLVM:
* [https://youtu.be/VynWyOIb6Bk](https://youtu.be/VynWyOIb6Bk)
* [https://youtu.be/sjnp3P9x5jA](https://youtu.be/sjnp3P9x5jA)
* [https://youtu.be/d67kfSnhbpA](https://youtu.be/d67kfSnhbpA)

## Demo Link

You can try it out at the [Compiler Explorer](https://godbolt.org/z/z-x3Jj)

## Link to Code

You can follow the development [here](https://github.com/mgehre/llvm-project/).
URL CONTENT ANALYSIS TOOL
Tags: octograd2020
Published: 2020-05-20 09:34:00

[Comment]: # (All of this is placeholder text. Use this format or any other format of your choosing to best describe your project and experience.)

[Note]: # (If you used the GitHub Student Developer Pack on your project, add the "#githubsdp" tag above. We’d also love to know which services you used and how you used it!)

## I'VE BUILT A TOOL WHICH CAN TAKE INPUT AS URL AND CAN PREDICT THE CATEGORY OF THE URL TO WHICH IT BELONGS TO 


## Demo Link
https://drive.google.com/file/d/1NCkI7m_zQ4K7QTvfF8bRkcWdfULjZCX9/view?usp=sharing 
 

## Link to Code

{% github https://github.com/thecoderxman/Url-Content-Analysis %}

[Note]: # (Our markdown editor supports pretty embeds. If you're sharing a GitHub repo, try this syntax: `{% github link_to_your_repo %}`)

## How I built it ?
I built it using Natural Language Processing and Machine Learning along with Web Scrapper(for which I've used beautifulsoup)


## Excited to share my first post on DEV



[Final Note]: # (CONGRATULATIONS!!! You are amazing!)