Tia  Gottlieb

Tia Gottlieb

1596998880

Everything You Always Wanted to Know About Derivatives

You’re sitting in a classroom. You look around and see your friends writing something down. It seems they are taking the exam, and they know all the answers (even Johnny who, how to say it… wasn’t the brilliant one). You realize that your exam is in front of you, and it’s Maths. You start reading it but you don’t understand a thing. That’s terrible, your heart speeds up, you’re sweating and then… you wake up.

Uff, it was only a dream. You get back to sleep, but one thing bothers you. This paper from a dream, there was something about… how is it called… derivatives? You remember you learned it by heart at school, but never truly understood it. It’s time to face this ghost from the past.

Don’t be afraid, it’s there for a while

The idea of the derivative is not new. There is a little bit of controversy about the inventor of derivatives. The battle is between Sir Isaac Newton and Gottfried Wilhelm Leibniz.

Apparently, these two great minds discovered it independently, not being aware of their colleagues’ work. What’s interesting they came to similar conclusions having completely different ideas and approaches to the problems they were trying to solve[1].

Newton thought in the context of physics and motion, while Leibniz thought in terms of formula that could describe a change in the metaphysical meaning. However, people worked on similar theorems before the 17th century, when Newton & Leibniz lived. Arab and Persian mathematicians from the 11th and 12th centuries are supposed to discover basic ideas behind derivatives[2].

And it’s useful!

Image for post

If you have ever been wondering if you’ll use any of the things you learned at school in real life, the answer is yes, derivatives are such a thing. Nowadays they are an important part of algorithms in many innovative areas, like Artificial Intelligence. In Machine Learning which is one of the AI domains, derivatives help computer programs to learn.

Generally speaking, such algorithms optimize objective functions (very often derivatives are needed for this purpose) so programs can find optimal parameters to solve different tasks (e.g. recognizing people on photos). Let’s get the key idea behind derivatives.

#derivatives #math #data-science #learning #mathematics #deep learning

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Everything You Always Wanted to Know About Derivatives
Tia  Gottlieb

Tia Gottlieb

1596998880

Everything You Always Wanted to Know About Derivatives

You’re sitting in a classroom. You look around and see your friends writing something down. It seems they are taking the exam, and they know all the answers (even Johnny who, how to say it… wasn’t the brilliant one). You realize that your exam is in front of you, and it’s Maths. You start reading it but you don’t understand a thing. That’s terrible, your heart speeds up, you’re sweating and then… you wake up.

Uff, it was only a dream. You get back to sleep, but one thing bothers you. This paper from a dream, there was something about… how is it called… derivatives? You remember you learned it by heart at school, but never truly understood it. It’s time to face this ghost from the past.

Don’t be afraid, it’s there for a while

The idea of the derivative is not new. There is a little bit of controversy about the inventor of derivatives. The battle is between Sir Isaac Newton and Gottfried Wilhelm Leibniz.

Apparently, these two great minds discovered it independently, not being aware of their colleagues’ work. What’s interesting they came to similar conclusions having completely different ideas and approaches to the problems they were trying to solve[1].

Newton thought in the context of physics and motion, while Leibniz thought in terms of formula that could describe a change in the metaphysical meaning. However, people worked on similar theorems before the 17th century, when Newton & Leibniz lived. Arab and Persian mathematicians from the 11th and 12th centuries are supposed to discover basic ideas behind derivatives[2].

And it’s useful!

Image for post

If you have ever been wondering if you’ll use any of the things you learned at school in real life, the answer is yes, derivatives are such a thing. Nowadays they are an important part of algorithms in many innovative areas, like Artificial Intelligence. In Machine Learning which is one of the AI domains, derivatives help computer programs to learn.

Generally speaking, such algorithms optimize objective functions (very often derivatives are needed for this purpose) so programs can find optimal parameters to solve different tasks (e.g. recognizing people on photos). Let’s get the key idea behind derivatives.

#derivatives #math #data-science #learning #mathematics #deep learning

A reliable Cryptocurrency Derivatives Exchange Development company

Antier Solutions is consider as one of the best Cryptocurrency Derivatives Exchange Development company that is specialized in offering world’s best cryptocurrency Derivatives Exchange Development Services that enables the following 4 key types- Futures trading, Forwards trading, Options trading, and Perpetual trading. Our skilled team of blockchain developers build Derivative exchange on both centralized and decentralized platform. It’s your choice to build the best one for you. Exchange owners can leverage the potential of a cryptocurrency derivatives exchange to reach more investors. A Crypto derivative trading platform is more flexible than Spot Margin trading and opens access to otherwise unavailable markets. To know more about us, feel free to visit us.

#cryptocurrency derivatives exchange #crypto derivatives exchange development #cryptocurrency derivatives exchange development #derivatives exchange development services #derivative exchange development company

Ian  Robinson

Ian Robinson

1624434540

Everything You Need to Know about Apache Storm

The ever-increasing growth in the production and analytics of Big Data keeps presenting new challenges, and the data scientists and programmers gracefully take it in their stride – by constantly improving the applications developed by them. One such problem was that of real-time streaming. Real-time data holds extremely high value for businesses, but it has a time-window after which it loses its value – an expiry date, if you will. If the value of this real-time data is not realised within the window, no usable information can be extracted from it. This real-time data comes in quickly and continuously, therefore the term “Streaming”.

Analytics of this real-time data can help you stay updated on what’s happening right now, such as the number of people reading your blog post, or the number of people visiting your Facebook page. Although it might sound like just a “nice-to-have” feature, in practice, It is essential. Imagine you’re a part of an Ad Agency performing real-time analytics on your ad-campaigns – that the client paid heavily for. Real-time analytics can keep you posted on how is your Ad performing in the market, how the users are responding to it, and other things of that nature. Quite an essential tool if you think of it this way, right?

Looking at the value that real-time data holds, organisations started coming up with various real-time data analytics tools. In this article, we’ll be talking about one of those – Apache Storm. We’ll look at what it is, the architecture of a typical storm application, it’s core components (also known as abstractions), and its real life-use cases.

Let’s go!

Table of Contents

#big data #data #technical skills #technology #everything you need to know about apache storm #apache storm

Anastasia soda

Anastasia soda

1623283200

Hedgefunds don't want you to know they're being margin called and liquidated- GME UP

Overview
In January 2021, retail investors on social media site Reddit’s “WallStreetBets”
subchannel (“subreddit”) collectively executed an investment strategy to induce a short squeeze
in stocks such as GameStop, AMC and KOSS, as well as other securities they identified as being
heavily shorted by hedge funds. Meaning, social media users collectively drove the stock prices
up, forcing short sellers who bet the stock price would go down, to purchase shares at an
increased price. Reddit user, Keith Gill, notoriously discussed GameStop stock on Reddit under
the username “DeepF*ckingValue.” Initially, this squeeze led to heavy losses for some short
sellers, particularly hedge funds, and led to substantial financial gain for some retail investors.
Robinhood, and other broker dealers, placed restrictions on transactions in these stocks, which
received public and regulatory scrutiny. Eventually, the stock prices started to decline and many
investors were faced with steep financial losses. For some, the January short squeeze raises
questions regarding whether legislators and regulators should take a closer look at existing rules
governing short sales and related disclosures, as well as the conflicts between the practice of
payment for order flow and firms’ best execution obligations. It also raises important questions
about the efficacy of anti-market manipulation laws and whether technology and social media
have outpaced regulation in a manner that leaves investors and the markets exposed to
unnecessary risks.
📺 The video in this post was made by tametheark
The origin of the article: https://www.youtube.com/watch?v=VQSUrDiymJA
🔺 DISCLAIMER: The article is for information sharing. The content of this video is solely the opinions of the speaker who is not a licensed financial advisor or registered investment advisor. Not investment advice or legal advice.
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Thanks for visiting and watching! Please don’t forget to leave a like, comment and share!

#bitcoin #blockchain #hedgefunds #hedgefunds don't want you to know they're being margin called #liquidated

Anastasia soda

Anastasia soda

1623286800

Hedgefunds don't want you to know they're being margin called and liquidated-What it means

Overview
In January 2021, retail investors on social media site Reddit’s “WallStreetBets”
subchannel (“subreddit”) collectively executed an investment strategy to induce a short squeeze
in stocks such as GameStop, AMC and KOSS, as well as other securities they identified as being
heavily shorted by hedge funds. Meaning, social media users collectively drove the stock prices
up, forcing short sellers who bet the stock price would go down, to purchase shares at an
increased price. Reddit user, Keith Gill, notoriously discussed GameStop stock on Reddit under
the username “DeepF*ckingValue.” Initially, this squeeze led to heavy losses for some short
sellers, particularly hedge funds, and led to substantial financial gain for some retail investors.
Robinhood, and other broker dealers, placed restrictions on transactions in these stocks, which
received public and regulatory scrutiny. Eventually, the stock prices started to decline and many
investors were faced with steep financial losses. For some, the January short squeeze raises
questions regarding whether legislators and regulators should take a closer look at existing rules
governing short sales and related disclosures, as well as the conflicts between the practice of
payment for order flow and firms’ best execution obligations. It also raises important questions
about the efficacy of anti-market manipulation laws and whether technology and social media
have outpaced regulation in a manner that leaves investors and the markets exposed to
unnecessary risks.

#bitcoin #blockchain #liquidated #hedgefunds #hedgefunds don't want you to know they're being margin called