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Tenacia Wenzel
Tenacia Wenzel
Aug 13, 2018
#LOVE-NEST-(MINADUKI-YUU) chapter 1 is missing
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Bella E
Bella E
Aug 13, 2018
#FENG-NI-TIAN-XIAI love it but the some chapters are missing it makes the story hard to follow sometimes
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ketotonedietreviews
ketotonedietreviews
Mar 09, 2019
When you start out on your Keto Tone Shark Tank, your body will feel fatigued, you may be moody from missing carbs, and you may be finding it difficult to focus. This is because your body isn’t accustomed to a Keto lifestyle yet. So Keto Tone Shark Tank helps to reduce your weight.
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ishan09
ishan09
Dec 07, 2022
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.
data science classes in pune
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.

data science training in pune

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
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Alan Luiz
Alan Luiz
Aug 15, 2022
Ukraine War: The Donbas body collector who has lost count
Aleksey Yukov standing next to the white van, marked with a red cross
Image caption,
Aleksey Yukov and his men recover dead bodies of Ukrainian and Russian soldiers killed in combat in the Donbas
Aleksey Yukov has lost count of the bodies he's recovered in the Donbas over the past five months. He says he thinks it's more than 300, but he can't be sure.

Aleksey and his men drive a refrigerated white van, marked with a red cross, to carry out their work. They often drive towards danger to collect the bodies and remains of dead Ukrainian and Russian troops and civilians.

"We work with no days off. Constantly. We drive, we investigate, we transport, we search, all the time," he says.

It's grim work too - digging up the decomposing bodies of Russian soldiers buried in shallow trenches, or gathering their remains from burnt out armoured vehicles.

According to the United Nations, more than 5,000 Ukrainian civilians have been killed since Russia invaded in February.

There are no official figures for how many Ukrainian troops have died. But one adviser to President Zelensky told the BBC last month that between 100-200 Ukrainian soldiers were being killed every day. On average it's at the lower end of that scale.


Aleksey says that figure sounds realistic to him. But he believes the Russians are losing three times that number.

One Ukrainian soldier we spoke to, who had fought in Severodonetsk, described Russian tactics as similar to the First World War - with waves of their infantry running into a hail of bullets.

Smoke rising near homes in Donbas
Image caption,
Smoke rises near homes in the eastern Donbas region, where Russia has targeted its ground offensive
Who does Aleksey think is winning the war? "It's not about who is winning," he says. "It's about who's right. They [Russia] came here and that was unforgivable".

Every Ukrainian soldier we spoke to said they still believed they could win. Even in units that had suffered combat casualties of more than half of the troops.

But it's taking its toll on the living as well as the dead. Aleksey hasn't seen his one-year-old daughter for months.

"This war has ruined the life you had and the one you've been building," he says.


He adds that at the end of the day it all catches up: "That feeling when you are empty inside. The unfillable void".

Why Russia wants to seize Ukraine's eastern Donbas
Death comes quickly in the Donbas. Russian shells take mere seconds to land, and they're being used in industrial quantities. On average Russia is firing 20,000 artillery shells a day. Ukraine is able to respond with just 6,000.

There's no respite from the sound of heavy shelling at a military medical station we visit. The chief medical officer - who only wants to be known as Dr Anatoliy for his own safety - describes the situation on the frontline as "fragile".

He shows us photographs of a badly damaged military ambulance - riddled with bullet holes and torn to shreds by shrapnel. Dr Anatoliy says the red cross painted on their vehicles mean nothing to Russians. Two more ambulances are waiting outside the building under camouflage nets - ready to go to pick up the injured.

Tina packing a military bag inside an ambulance
Image caption,
Before volunteering to join the army Tina worked at a children's hospital
We meet Tina and Polina, two front line medics.

Tina used to work at a children's hospital before she volunteered to join the army. She wipes away tears as she talks about the family she's now missing.


"The pain goes away, because you have a task: to get a person to a hospital alive" she says. I ask if she's scared. "Of course it's scary. When a shell lands nearby, everything shrinks inside you".

For every soldier killed many more are injured. Tina says she's not allowed to give numbers but adds "there are casualties almost every day, and not just one. Sometimes many, sometimes a lot".

Polina standing near a vehicle
Image caption,
Twenty-one-year-old Polina says she exercises and listens to music to keep some sense of normality
Polina is just 21. The war's already cast a big shadow over her short life.

Her father and uncle are now prisoners in Russian-occupied Ukraine. She says she's trying her best not to let it get her down. She exercises and listens to music whenever she can - just to keep some sense of normality.

But Polina admits it's hard not to feel gloomy and depressed: "Apart from the bullets flying over your head, wounded people - and those wounded are often my friends and buddies - if you're taking it to heart it's going to be tough".

It's the troops she treats who give her hope.

"The guys who are injured and exhausted don't even want to go to hospital sometimes. They say I'm not going to leave my mates, we're holding the line together".

line
War in Ukraine: More coverage
RUSSIA: Stop the fighting: Russian soldier's mum speaks out
WATCH: War nears Ukraine maternity ward
ANALYSIS: Is the tank doomed?
READ MORE: Full coverage of the crisis
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™~°OTAKU°~™
™~°OTAKU°~™
May 17, 2021
wow
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Yayoi: kitsune del yaoi
Yayoi: kitsune del yaoi
May 06, 2021
Esto es muy interesante, un poco difícil así que terminare de instalarme y comenzar a subir mas capítulos....
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Norkelly Guzman Hilario
Norkelly Guzman Hilario
May 15, 2021
diamantes gratis
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quirkyewe
quirkyewe
May 14, 2021
𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍𑁍
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𝚄𝙲𝙷𝙸𝙷𝙰__𝙽𝙾𝙾𝚁 🥀✨
𝚄𝙲𝙷𝙸𝙷𝙰__𝙽𝙾𝙾𝚁 🥀✨
May 13, 2021
cute 😭💕
hehe 🍥🍡✨
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Jalon George
Jalon George
May 11, 2021
Hi
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Facundo Correa61608
Facundo Correa61608
May 02, 2021
hhsjkskso
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Selena Md
Selena Md
Apr 30, 2021
진실은, 그녀는 귀엽다.
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Ail Ajm
Ail Ajm
Apr 29, 2021
kgkoi@Silva React
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Miguel Antonio Cabezas Chamorro
Miguel Antonio Cabezas Chamorro
Apr 28, 2021
Hola soy nuevo espero llevarme bien con todos😁😁😁
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bjr._.toi._
bjr._.toi._
Apr 28, 2021
Sakura Yamauchi ✨
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Astro6
Astro6
Apr 28, 2021
erza❤
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Aya Halouma Bouacha
Aya Halouma Bouacha
May 29, 2021
Vietsub] [Ma Đạo Tổ Sư] Đông phong chí - Vong Tiện/Nhiếp Dao/Song đạo trưởng
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Desca Mangas
Desca Mangas
May 28, 2021
Salut, tu peux aller liker mes vidéos youtube et t’abonner stp ?
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Desca Mangas
Desca Mangas
May 27, 2021
Hola, ¿puedes hacer me gusta en mis videos de youtube y suscribirte, por favor?
https://youtube.com/channel/UC3FCRr6lkkS_HRds5Rm7swg
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