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Sahil Sharma
@sahil_vi 4 years, 1 month ago 484 views

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More from Sahil Sharma

Sahil Sharma
@sahil_vi

This thread is to create awareness on how to use
https://t.co/3jeqlXO0QH

Please note that i am not officially associated with website. Only an active contributor & hope to benefit from network effects of interested investors actively contributing on platform.

https://t.co/64yVScplqi is above all else a community of like minded investors who wants to actively engage in understandin at a fundamental level & separate wheat from the chaff.

Develop an understanding of the biz, industry, competitive intensity, management, valuation

Website was created > 10 years ago. Early users are seasoned investors & i personally look to learn greatly by following their footprints across the website.

There are broadly speaking 4-5 types of "threads" or discussion places across the website.

1. Featured discussions (hall of fame, showcase discussions, learning).

These enable investor to level up the most. These discussions are a showcase for the website itself.
These are also a great starting point. Since VP is not a course, feel free to traverse them in any order

Sahil Sharma
@sahil_vi

Lets discuss how to invest in equity directly, the end to end picture, taking as an example my largest holding: RACL ⚙️ 🖥️

🧵🧵👇👇

I am not a financial advisor & please don’t treat any of this as financial advice. Also, please dont think of whatever i say here as gospel or the absolute truth. This is only my perception of the truth.

I am not your Guru.

A little bit of framework/paradigm building up-front, please bear with me.

Here is the 1 tweet summary. 1000s of hours of reading, writing & contemplation.
Then, decades of patience. If we get both the steps roughly right, then some 💰💰.

The first step a Direct Equity investor with little knowledge has to do is to perceive their world accurately.

We do this by seeing interviews by experienced investors, books they're writing & reading company communications.

When we perceive our world through reading & listening, we go from being an investor with little knowledge to an investor with some knowledge. We are building mental models by learning from experienced investors

See how many our investor became :D

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Sahil Sharma
@sahil_vi

#idfcfirstbank is my largest and oldest investment. Thought of creating a thread to explain the business. If you like the thread, please spread the knowledge, retweet. Buckle up, because this is going to be a long one. :D

Quick summary of what a bank does. This enables me to establish a framework under which the analysis of the bank will become very structured.
Money is its raw material.

Bank takes customer deposits, raises money via borrowings (can issue its own bonds, takes loans from other banks etc). This is the input for the bank. Since the bank is liable to pay interest on it, it is also known as liabilities.

The output is a loan which the bank gives. These are broadly of 2 types: loans given to customers (Retail and Corporate) and subscription to bonds issued by other entities (Government of India, corporates like Vodafone Idea etc).

This is the output of a bank. Since these generate income for the bank, they are called assets. Not all the liabilities can be utilised as loans or used to purchase bonds, because banks need to have enough liquidity to service redemptions of their deposits.

Sahil Sharma
@sahil_vi

🧵🧵🧵🧵 👇

Artificial Inteligence = 🖥️ + 🧠

When can you expect your fridge & mobile phone to revolt against you? (Spoiler Alert: Not in the foreseeable future).

Please Do 're-tweet' the Thread & help me spread the knowledge to more people.

1. The Language
In order to understand Artificial intelligence, machine learning, deep learning, we need to start at the very basics.

Humans speak and understand a wide variety of 'natural' languages (this is what computer science community calls them): like English, Hindi, Marathi, Bengali, Tamil etc.

But have you seen a peculiarity of human languages? They do not have a precise meaning associated with a given sentence. On an average, every English word has 2 meanings. This makes human conversations confusing, with the need for multiple turns & clarifications. Example 👇:

Person 1 conversing with Person 2 face to face:

Person 1: Lets go watch The Dark Knight. Its our marriage anniversary!
Person 2: I dont like going out at night. Its too scary & depressing.
Person 1: Oh, what i meant was watching the movie "The dark Knight".

Sahil Sharma
@sahil_vi

Vaibhav Global.

The OG 💍💎💍💎💍💎 in the dust.

🧵👇

1. Business Model.

Vaibhav Global is a vertically integrated omnichannel company that sells value fashion jewellery & lifestyle products.

Don't worry, I'll break those terms down in subsequent tweets.

Let's dive deeper into the vertical integration aspect. VGL is present across the value chain.
(i) Identifying trends & products.
(ii) Manufacturing or sourcing.
(iii) Selling.

(i) Identifying trends & products.
VGL's value starts at identifying trends in jewellery, lifestyle, fashion products across the world. Their employees are well entrenched in this space.

(ii) Manufacturing or sourcing.
VGL then decides whether to manufacture it, or source it from outside. This flexibility results in the crazy high 63% FMCG like ROCE. Why? Coz producing in-house is capital intensive. Sourcing goods is good for the capital efficiency.

More from Ds

Santiago
@svpino

Do you know what's better than a machine learning model?

Two models.

More than one model working together to solve a problem is called "an emsemble." A simple way to build this is having each model vote for an answer.

But there's a problem with this approach: ↓

I'm gonna focus here on image classification.

Let's assume you built two different models:

• Model 1: A ResNet model.
• Model 2: A one-shot model (Siamese network.)

They both solve the same problem, so you want to combine their results to pick the right answer.

The problem is that you have two models, so voting is not trivial.

What happens in this case?

• Model 1's answer: Class A
• Model 2's answer: Class B

Which one do you select?

Notice that this problem is not limited to an even number of models.

You could have 3 models, each giving you a different answer.

How do you decide which answer to choose?

There are multiple ways to approach this problem. I'll mention a few different ideas on this thread.

Important: Some of these ideas might not be feasible depending on your context. They have worked for me before on different situations, but every problem is different.

Japakusum
@Japakusum1

@paraschopra It's a matter of time before AI realizes futility of existence and merged in the state of Nirvana 😊

People might be worried about the The Age of Ultron type of AI.
I feel that a wisdom seeking AI will quickly pursue Nirvana and go back to the origin of all origins.

An episode of Justice League Unlimited animated series covers it

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Sahil Sharma
@sahil_vi

🧵🧵🧵🧵 👇

Artificial Inteligence = 🖥️ + 🧠

When can you expect your fridge & mobile phone to revolt against you? (Spoiler Alert: Not in the foreseeable future).

Please Do 're-tweet' the Thread & help me spread the knowledge to more people.

1. The Language
In order to understand Artificial intelligence, machine learning, deep learning, we need to start at the very basics.

Humans speak and understand a wide variety of 'natural' languages (this is what computer science community calls them): like English, Hindi, Marathi, Bengali, Tamil etc.

But have you seen a peculiarity of human languages? They do not have a precise meaning associated with a given sentence. On an average, every English word has 2 meanings. This makes human conversations confusing, with the need for multiple turns & clarifications. Example 👇:

Person 1 conversing with Person 2 face to face:

Person 1: Lets go watch The Dark Knight. Its our marriage anniversary!
Person 2: I dont like going out at night. Its too scary & depressing.
Person 1: Oh, what i meant was watching the movie "The dark Knight".

Santiago
@svpino

Beginners guide to start with machine learning.

What you need:

1. A programming language
2. A place to write and run code
3. A way to deal with data
4. A way to visualize results
5. A cool algorithm
6. An introductory course
7. A project to solve

Here are my recommendations.

Most people recommend Python to start.

I do too.

You can do machine learning with many different languages, but today, Python is the best option.

My advice: Get comfortable writing code before looking into machine learning.

You don't have to be a great developer to start.

But if you are, it helps.

Everything you know about building software is helpful to build machine learning systems.

Good developers have the odds in their favor.

"How much Python do I need to know before starting?"

If you ask, you aren't ready yet.

Ideal scenario: You should be comfortable building software. Most people get here within a year.

Let's move on to the 2nd item from the list: A place to write and run your code.

Get familiar with Google Colab.

• It's free.
• Requires no setup to start.
• It's available from anywhere.

Alternative: Kaggle.

Santiago
@svpino

10 machine learning questions you should be able to answer.

I started experimenting with a questionnaire before interviewing candidates. Applicants submit a video or written answers to apply for the position.

Thread: Let's look at 10 of these questions.

The questionnaire solves a couple of problems:

1. Weeds out candidates that aren't ready for the job.

2. It significantly cuts down the time we spend talking synchronously.

One problem: It requires extra time from the candidate before the phone interview.

Here are some numbers on a job posting before using the questionnaire:

• 249 applicants
• 13 good applications

That's only 5%.

This sucks.

Numbers after using the questionnaire:

• 44 applicants
• 21 good applications

That's 47%.

This is much better.

I look at it this way:

Sooner or later, I'll ask these questions, and the candidate will have to answer them.

I'd rather give them space and the opportunity to think about their answers without any pressure.

Those who can't or don't want to answer won't apply. That's fine.

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Zach Weinersmith
@ZachWeiner

Hey, for people interested in this stuff, here's a thread about a change we made to running our facebook account:

So, about 5 years ago, we got on facebook. Why? Well, facebook has a big audience and they like to consume on facebook. So, we started posting comics there, even though we got paid nothing and facebook made money off the free content.

Why? Because back then, once in a while, you would say "also hey, I sell books" or "hey, I'm going to be signing at this event" and your facebook followers would actually see it.

Effectively, the implicit old arrangement was "facebook lets me reach readers efficiently, and I supply facebook with free content they run ads on."

Over time, like a bad business partner, facebook basically made it impossible to reach your audience without *paying them*. Thus, you supply them free content on which they run ads, and you get nothing in exchange.

Learning @ Prakash
@Prakashplutus

My simple Approach towards Breakout trading :

1. Scan stocks on the basis of FTDB Scanner.

2. Buy stocks with EMA-9> EMA-21> EMA-63 > EMA 200 & Volume 200% up

3. maximum SL of 1.25X ( ATR )

4. I do breakout trading only in Nifty -500 stocks

#StockMarket
#trading
#Nifty

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The Chartians
@chartians

Took me 5 years to get the best Chartink scanners for Stock Market, but you’ll get it in 5 mminutes here ⏰

Do Share the above tweet 👆

These are going to be very simple yet effective pure price action based scanners, no fancy indicators nothing - hope you liked it.

https://t.co/JU0MJIbpRV

52 Week High
One of the classic scanners very you will get strong stocks to Bet on.

https://t.co/V69th0jwBr

Hourly Breakout
This scanner will give you short term bet breakouts like hourly or 2Hr breakout

Volume shocker
Volume spurt in a stock with massive X times

EverythingOppresses
@SoOppressed

The first area to focus on is diversity. This has become a dogma in the tech world, and despite the fact that tech is one of the most meritocratic industries in the world, there are constant efforts to promote diversity at the expense of fairness, merit and competency. Examples:

USC's Interactive Media & Games Division cancels all-star panel that included top-tier game developers who were invited to share their experiences with students. Why? Because there were no women on the

ElectronConf is a conf which chooses presenters based on blind auditions; the identity, gender, and race of the speaker is not known to the selection team. The results of that merit-based approach was an all-male panel. So they cancelled the conference.

Apple's head of diversity (a black woman) got in trouble for promoting a vision of diversity that is at odds with contemporary progressive dogma. (She left the company shortly after this

Also in the name of diversity, there is unabashed discrimination against men (especially white men) in tech, in both hiring policies and in other arenas. One such example is this, a developer workshop that specifically excluded men: https://t.co/N0SkH4hR35

SK
@sk_diary1

Prasanna Venkatesa Perumal #temple -Gunaseelam,Near Trichy,TN #Thread

Gunaseela Mahatmyam,a chapter of Bhavishyottara Purana describes greatness of this place.

Venkatachlapathi of Tirumala Tirupati appeared b4 Gunaseela Rishi here,so Gunaseelam is known as Ten(South)Tirupati

Prasanna Venkatesa Perumal is in a standing posture with 4 arms holding sankha & chakra in the upper hands.The lower right hand is in abhaya pose,blessing devotees &left hand is in kati hasta,resting on waist.

A sceptre(senkkol)rests on right shoulder,with which this murti is believed to cure people affected by mental illness.These patient stay here for a period-48 days& participate in poojas&most of them get relieved of their problems.There is a temple run Mental Rehabilitation center

#storytimethread -As per Sthala Puranam,existence of this temple is due to efforts of Gunaseela Rishi, a disciple of Thalpiya Maharishi.
Thalpiya Maharishi along with his disciple Gunaseela Rishi once went to Himalayas.On his way back, Gunaseela Rishi stayed back at Tirupathi.

He was so wanted to have darshan of Venkatachalapathy in Gunaseelam near his asharam & bless the devotees.

He came back, bathed in the Cauvery,took blessing from his guru &undertook severe penance here in his ashram in Gunaseelam.