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What is Topic Modeling?

Topic modeling is a type of statistical modeling for discovering the abstract “topics” that occur in a collection of documents. Topic Models are, in a nutshell, a type of statistical language model used for uncovering hidden structures in a collection of texts.

In this article, we’ll cover LDA, and implement a basic topic model. Read More :- https://lakebrains.com/topic-modeling-in-python/

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Publish a browser extension to chrome store

Introduction

This blog gives a description about how you can upload your browser extension on the chrome web store. 

But before publishing it online you need to load and test your extension locally and check if its functionality is achieving what it is planned to.

Steps to publish browser extension :-

Register as a Chrome web developer

Create a zip folder 

Upload files

Add assets for listing

Submit files 

Registration

 To publish your extension on chrome web store you need to register as a chrome     web developer on chrome store.

Once, you register as a developer, you can setup your account by clicking on the account option as shown below:-

In this you can provide the information about your developer profile.

2. Create a Zip folder

To publish the extension you need to create a zip folder which contains the manifest file and other  files or items of your  browser extension.

The manifest file must specify the following elements:-

“name” – The  value of this element is the name appear in the chrome web

                  store.

“version”-  This tells the version of the extension

“items”-This specifies the icons your extension uses.   

“description”- It is a string which describes about your extension .

3. Upload files

Steps to upload files are-

Go to Chrome’s developer dashboard.

Click on the Add new items button

Click on choose file > your zip file > upload

4. Add assets

You need to fill the information’s of the tabs present on the left hand corner of the tab.

Package tab – This tab displays the information about the items being   uploaded.

Store listing tab – It contains the details of the uploaded items and how it  

Should appear in the browser extension. It contains details like product details, graphic assets.

Privacy - this tab describes about what the extension is all about and justify the permission.

Payment and distribution- In this section you can set that is your extension is free or does it need to be purchased  and even you can set the visibility of your extension i.e. you can choose who can see your extension.

5. Submit the files

To publish your extension click on the submit for review button.

After submitting for review it will undergo a review process.

Conclusion

Publishing a browser extension to the chrome store is a great way to increase your visibility and reach. With over 1 billion active users, Chrome is one of the most popular browsers in the world. If you can get your extension in front of even a small fraction of those users, you could see a significant increase in traffic and engagement. The process of publishing an extension is relatively simple and only takes a few minutes. Once you've created your account and submitted your extension, it will be reviewed by the Chrome team. If everything looks good, your extension will be approved and made available to all Chrome users.

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Blogs - Lakebrains Technologies

Learn our insights & technologies in the field of Web Development, Cloud, Computer vision, Web Scraping. Digital Marketing & Data science" Lakebrains a company provides services in the area of web design and development, digital marketing, data science and computer vision to help your business grow multiple folds. Our team consist of experienced professional which are excited about the technologies and its impact in driving growth of its customer.

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Problems Faced by NLP Practitioners and Developers

The majority of the difficulties come from data complexity as well as features like sparsity, variety, and dimensionality, and therefore the dynamic properties of the datasets. NLP continues to be a young technology; therefore, there’s plenty of room for engineers and businesses to tackle the many unsolved problems that include deploying NLP systems.

Introduction To NLP

NLP is a branch of computer science or artificial intelligence that deals with a way to manage communication between machines and humans using natural language. NLP includes machines or robots that understand human language, the way we speak, so they can truly communicate with us. It implies the natural processing of human language. You probably heard these names in some places: Google Assistant, Siri, Alexa, and Cortana. Presently, it is the right time to add another option to this list.

LakeBrains Technologies

LakeBrains Technologies is an AI-powered innovative product development company. Lakebrains has developed deep expertise in the development of NLP Service Provider Company (Sentiment & Behavior Analysis), Web Application, Browser Extension Development, and HubSpot-CMS. In our short period of spam, we have majorly worked on SaaS-based applications in sales, customer care, and the HR field.

1. Training Data

NLP is principally about studying the language, and to be proficient, it’s essential to spend a considerable amount of time listening to, reading, and understanding it. NLP systems target skewed and inaccurate data to find out inefficiently and incorrectly.

2. Development Time

The total time taken to develop an NLP system is higher. AI evaluates the info points to process them and use them accordingly. The GPUs and deep networks work on training the datasets, which will be reduced by some hours. The per-existing NLP technologies can help in developing the merchandise from scratch.

3. Language Differences

In the United States, the majority speak English, but if you’re thinking of reaching a global and/or multicultural audience, you’ll have to provide support for multiple languages. Different languages have not only vastly different sets of vocabulary but also differing types of phrasing, different modes of inflection, and different cultural expectations. You’ll be able to resolve this issue with the assistance of “universal” models that may transfer a minimum of some learning to other languages. However, you’ll still have to spend time retraining your NLP system for every new language.

4. Phrasing Ambiguities

Sometimes, it’s hard for an additional creature to parse out what someone means once they say something ambiguous. There might not be a transparent, concise aspiring to be found in a very strict analysis of their words. So as to resolve this, an NLP system must be ready to seek context that will help it understand the phrasing. It should also have to ask the user for clarity.

5. Misspellings

Misspellings are a straightforward problem for human beings; we are able to easily associate a misspelled word with its properly spelled counterpart, and seamlessly understand the remainder of the sentence within which it’s used. Except for a machine, misspellings may be harder to spot. You must use an NLP tool with the capability to acknowledge common misspellings of words and move beyond them.

6. Innate biases

In some cases, NLP tools can carry the biases of their programmers as well as biases within the information sets that train them. An NLP could exploit and/or reinforce societal biases, or it could provide a better experience to some users than others. It’s challenging to form a system that works equally well in all situations with all people.

7. Words with Multiple Meaning

No language is ideal, and most languages have words that might have multiple meanings depending on the context. For instance, a user who asks, “how are you?” incorporates a totally different goal than a user who asks something like “how do I add a replacement credit card?” With the help of context, good NLP technologies should be able to distinguish between these sentences.

8. Phrases with multiple intentions

Some phrases and questions even have multiple intentions, so your NLP system can’t oversimplify matters by interpreting only one of these intentions. As an example, a user may prompt your chatbot with something like, “I must cancel my previous order and update my card on file.” Your AI must be able to distinguish these intentions separately.

9. False positives and uncertainty

A false positive occurs when an NLP notices a phrase that ought to be understandable and/or addressable but can not be sufficiently answered. The answer here is to develop an NLP system that may recognize its own limitations and use questions or prompts to clear up the paradox.

10. Keep a Conversation Moving

Many modern NLP applications are built on dialogue between people and machines. Accordingly, your NLP AI must be able to keep the conversation moving, providing additional inquiries to collect more information and always pointing toward an answer.

Conclusion

Natural Language Processing is the practice of training machines to understand and interpret conversational contributions from people. NLP-supported Machine Learning is also accustomed to establishing communication channels between humans and machines. NLP can assist organizations and people with saving time, further developing proficiency, and increasing consumer loyalty.

While natural language processing has its drawbacks, it still provides plenty of benefits for each company. Many of those obstacles are going to be torn down within the next few years as new approaches and technology emerge on a daily basis. Machine learning techniques supported by linguistic communication processing could also be used to evaluate large quantities of text in real-time for previously unobtainable insights.

If you’re managing a project utilizing NLP, one of the best ways to tackle these problems is to use a set of NLP tools that exist already and might facilitate your solving a number of these hurdles quickly. Utilize the efforts and creativity of others to supply a stronger product for your consumers.

LakeBrains Technologies

LakeBrains Technologies is an AI-powered innovative product development company. Lakebrains has developed deep expertise in the development of NLP Service Provider Company (Sentiment & Behavior Analysis), Web Application, Browser Extension Development, and HubSpot-CMS. In our short period of spam, we have majorly worked on SaaS-based applications in sales, customer care, and the HR field.

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Data Visualization - Lakebrains Technologies

Data visualization services helps to communicate company’s data to business users using visual elements while emphasizing on the clarity.

Through the help of Data Visualization we can easily interpret increasingly larger batches of data. Machine Learning makes it easier to conduct predictive analysis

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Migrating Manifest V2 to V3

This blog lists changes being implemented as a part of Manifest V3, the next version of the Chrome Extensions platform. There are a lot of recent features and functional changes for extensions using Manifest V3.

But why Migrate to V3?

As chrome documentation says:- Extensions using MV3 will enjoy enhancements in security, privacy, and performance; they’ll also use contemporary Open Web technologies adopted in MV3, like service workers and promises.

# Updating the manifest.json file

Manifest Version

Service Worker 

In Manifest Version 3 background script is replaced by Service Worker. Write the “service_worker” under the "background" field

Manifest V3, which does not support more than one background script, if you want to add more, you can optionally declare the service worker as an ES Module by defining "type": "module", which allows you to import further code.

Service Worker One more way from which you’ll be able to include multiple files and call them from a service-worker.Js is to use the importScripts( ) method at the beginning of the service-worker.js script like this:-

Host Permission

In Manifest V3, you have to specify host permissions and optional host permissions separately from other permissions.

Actions

In an earlier version, actions were divided into “browser_action” and “page_action” keys. In Manifest V3, they’re unified into a single field named Action. This can be often done to scale back confusion between those two fields as they ultimately serve a common purpose.

  Here’s the V2 manifest:

Here’s the V3 manifest: -

Content security policy

It is a layer of security for the application. It helps you define all the origins from which you're loading any styles, scripts, or data. For every style, script, font, or connection, you have to specify the domains which you are loading in your application.

In MV2, we define “content_security_policy” as a string.

In Manifest V3 it’s an object with members representing alternative CSP contexts.

In Manifest V3:-

extension_pages: This covers pages in extension, including HTML files and service workers.

Sandbox: This covers any sandboxed extension pages that the extension uses.

Additionally, MV3 has put out of action certain Content Script Policy modifications that were allowed in MV2-

      The “script-src”,  “object-src” and “worker-src” may have only one of the resulting values:

self

none

Any localhost source

Web-accessible resources

To declare the packed resources that require to be accessed online, the web_accessible_resources will now not need an inventory of files. Instead, you’ll now provide a list of objects, each of which maps to a collection of resources like a group of URLs or extension IDs:

      In Manifest V2 the object should be like:-

            In Manifest V3 the object should be like:-

#API’S DEPRECIATED IN MV3

browserAction

chrome.pageAction

tabCapture

setTimeout

setInterval

chrome.declarativeWebRequest

chrome.app.runtime

chrome.app.window

appview

chrome.bluetooth

chrome.clipboard

chrome.extension.getExtensionTabs()

chrome.extension.lastError

chrome.extension.sendRequest()

chrome.tabs.getAllInWindow()

chrome.tabs.getSelected()

chrome.tabs.onActiveChanged

chrome.tabs.onHighlightChanged

chrome.tabs.onSelectionChanged

chrome.tabs.sendRequest()

chrome.tabs.Tab.selected()

chrome.extension.connect()

chrome.extension.onConnect

chrome.extension.onMessage

chrome.extension.sendMessage()

chrome.fileSystem

chrome.hid

chrome.extension.getURL()

chrome.mdns

chrome.mediaGalleries

chrome.networking.onc

chrome.extension.onRequest

chrome.extension.onRequestExternal

chrome.serial

chrome.socket

chrome.sockets.tcp

chrome.sockets.tcpServer

chrome.sockets.udp

chrome.sync.FileSystem

chrome.system.network

chrome.usb

chrome.virtualKeyboard

DOMParser

CONCLUSION

There are many changes between Manifest Version 2 and Manifest Version 3, and a lot of new features and functions are also added in Manifest Version 3 and many APIs which were supported in Manifest Version 2 are depreciated in Manifest Version 3.

One of the major changes is that the background script is being replaced by a service worker.

A new declarativeNetRequest API is introduced to handle network request modification.

Promise support has been added in Manifest Version 3.

In manifest version 3, an extension can only execute the javascript file which is included in the package; i.e. we cannot remotely host code.

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