Without A Daoist Partner, I Will Die

Hello, I am new here so there's few questions I have. I am confused how to submit a novel or something? Can anybody help? Thanks!

Help

How do i read Mangas here?
When ever i click on a chapter i only get the latest update page.

I am thinking of uploading a manga soon, but I would have to translate it into three languages. TT

#HERO-I-QUIT-A-LONG-TIME-AGOwhen is the next episode coming man I would like to read it 😉😊

I am try to upload a manga but it's stuck isn't getting upload doesn't matter how much I try.

Oiiii my name is sonnet and yes I am a boy and I translate BL manga into Portuguese :)

Channel promotion is very important, I have a good audience, but I would like more, but I'm still standing still.

#A-GOOD-DAY-TO-BE-A-DOGwahhhh. can I shout now? 😍😍😍

#A-World-That-I-Rule-¿Osea que? ¿ya termino o va a continuar esta gran historia?

The best foldable electric mountain bike is one that can be easily folded and transported without sacrificing too much in terms of quality or features. There are a number of foldable electric mountain bikes on the market, but not all of them are created equal. In order to help you make the best decision, we’ve put together a list of the best foldable electric mountain bikes currently available.

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#I-am-a-heroManga increíble de principio a fin, Hideo come back soon... :/

The simplest way to set up a talk radio station is to have a good microphone and digital recording program. You can then encode a program to be broadcasted and https://ascolta-radio.it/ upload it to a server. You will then have to wait a bit before you can start listening to your show. The most basic version of a radio app will have an encoding program which will capture the audio from your playback device and convert it to a format that can be streamed.

I hope you like this i drew this and it took a week to do it so i hope you like it

#Lord-Xue-Yingthis is great i love it.

P.S I hate the blood witch she is such a b**ch

Beginner’s Guide For The Data Scientist ?

data Science is a mix of different instruments, calculations, and AI standards to find concealed designs from crude information. What makes it not quite the same as measurements is that information researchers utilize different high-level AI calculations to distinguish the event of a specific occasion from now on. An Information Researcher will take a gander at the information from many points, some of the time points not known before.


data Perception

Information Perception is one of the main parts of information science. It is one of the fundamental apparatuses used to investigate and concentrate on connections between various factors. Information perception apparatuses like to disperse plots, line diagrams, bar plots, histograms, Q-Q plots, smooth densities, box plots, match plots, heat maps, and so on can be utilized for enlightening examination. Information perception is additionally utilized in AI for information preprocessing and examination, highlight determination, model structure, model testing, and model assessment.


Exceptions data science course in pune


An exception is a piece of information, that is totally different from the dataset. Exceptions are many times simply terrible information, made because of a broken down sensor, debased examinations, or human mistake in recording information. At times, exceptions could show something genuine like a glitch in a framework. Anomalies are extremely normal and are normal in enormous datasets. One familiar method for distinguishing exceptions in a dataset is by utilizing a container plot.


data Ascription

Most datasets contain missing qualities. The most straightforward method for managing missing information is just to discard the data of interest. Different addition procedures can be utilized for this reason to assess the missing qualities from the other preparation tests in the dataset. One of the most widely recognized addition methods is mean attribution where the missing worth is supplanted with the mean worth of the whole component section.


Information Scaling

Information scaling works on the quality and prescient force of the information model. Information scaling can be accomplished by normalizing or normalizing genuine esteemed info and result factors.
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There are two sorts of information scaling accessible standardization and normalization.



Head Part Examination

Huge datasets with hundreds or thousands of highlights frequently lead to overt repetitiveness particularly when elements are connected with one another. Preparing a model on a high-layered dataset having an excessive number of elements can at times prompt overfitting. Head Part Examination (PCA) is a factual strategy that is utilized for include extraction. PCA is utilized for high-layered and related information. The essential thought of PCA is to change the first space of elements into the space of the important part.


Direct Discriminant Investigation

The objective of the direct discriminant investigation is to find the component subspace that enhances class distinctness and diminishes dimensionality. Thus, LDA is a directed calculation.

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Information Apportioning

In AI, the dataset is frequently divided into preparing and testing sets. The model is prepared on the preparation dataset and afterward tried on the testing dataset. The testing dataset hence goes about as the concealed dataset, which can be utilized to gauge a speculation blunder (the mistake expected when the model is applied to a genuine world dataset after the model has been sent).


Regulated Learning

These are AI calculations that perform advancing by concentrating on the connection between the component factors and the known objective variable. Administered learning has two subcategories like ceaseless objective factors and discrete objective factors.




In unaided learning, unlabeled information or information of obscure construction are managed. Utilizing solo learning strategies, one can investigate the design of the information to extricate significant data without the direction of a known result variable or prize capability. K-implies bunching is an illustration of an unaided learning ca

#I-am-a-villager-what-about-it-kisamaaa como osas hacer llorar a la Loli

@AnimeClub @Manga dogs Well ...some users are publishing DC and Marvel comics lately (and they will publish even more).

I wanted to ask if this could bring problems to this page or not because of the copyright issue 😶.

Many users are very scared 😲 about this issue and I wanted to please clarify this matter as soon as possible.

As technology advances, universities and colleges around the world are finding new ways to use technology to improve the student experience. One such way is the use of chatbots powered by data science to help students with their inquiries. These chatbots can provide instant assistance to students and save time and resources for the college staff. In this article, we will explore the benefits of using a college enquiry chatbot powered by data science.
A college enquiry chatbot is an AI-powered chatbot that can provide students with instant answers to their inquiries about courses, admissions, fees, scholarships, and more. The chatbot uses natural language processing (NLP) and machine learning (ML) algorithms to understand and respond to student inquiries. These chatbots can also collect data on the types of inquiries and questions asked by students, which can be used to improve the services provided by the college.
One of the main benefits of using a college enquiry chatbot is the 24/7 availability it provides. Students can access the chatbot at any time of the day or night, without having to wait for a staff member to be available. This can be particularly useful for students who are located in different time zones or who have busy schedules that prevent them from making phone calls or visiting the college in person.
Another benefit of using a college enquiry chatbot is the speed at which it can provide answers. With the use of NLP and ML algorithms, the chatbot can understand the context of the student's inquiry and provide a relevant response within seconds. This can save students a lot of time and frustration compared to waiting on hold on the phone or sending an email and waiting for a response.
Data science plays a crucial role in the development and optimization of a college enquiry chatbot. The chatbot can be trained using historical data on the types of inquiries and questions asked by students. This data can be used to develop and refine the NLP and ML algorithms used by the chatbot to ensure accurate and relevant responses. As more data is collected, the chatbot can be further optimized to improve its accuracy and effectiveness.
One example of how data science can be used to optimize a college enquiry chatbot is through sentiment analysis. Sentiment analysis involves using ML algorithms to analyze the tone and emotion of a message. By analyzing the sentiment of the messages sent to the chatbot, the college can gain insights into the overall satisfaction of students with their experience. This information can then be used to identify areas for improvement in the services provided by the college.
Another example of how data science can be used in a college enquiry chatbot is through personalized recommendations. By analyzing the historical data on the types of inquiries and questions asked by students, the chatbot can provide personalized recommendations to students based on their previous interactions with the chatbot. This can help students find the information they need more quickly and easily.
In addition to improving the student experience, a college enquiry chatbot can also save time and resources for the college staff. By automating the process of answering common inquiries, staff members can focus on more complex tasks and provide better service to students who require additional assistance.
Overall, a college enquiry chatbot powered by data science can provide many benefits to students and staff alike. With its 24/7 availability, fast response times, and personalized recommendations, the chatbot can improve the student experience and save time and resources for the college staff. As data science continues to advance, we can expect to see even more innovative ways in which chatbots can be used to improve education and student services.
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