BC MACHINE LEARNING
Saved by @CodyyyGardner

Happy 2⃣0⃣2⃣1⃣ to all.🎇

For any Learning machines out there, here are a list of my fav online investing resources. Feel free to add yours.

Let's dive in.
⬇️⬇️⬇️

 Investing Services

✔️ @themotleyfool - @TMFStockAdvisor & @TMFRuleBreakers services

✔️ @7investing

✔️ @investing_city
https://t.co/9aUK1Tclw4

✔️ @MorningstarInc Premium

✔️ @SeekingAlpha Marketplaces (Check your area of interest, Free trials, Quality, track record...)
General Finance/Investing

✔️ @morganhousel
https://t.co/f1joTRaG55

✔️ @dollarsanddata
https://t.co/Mj1owkzRc8

✔️ @awealthofcs
https://t.co/y81KHfh8cn

✔️ @iancassel
https://t.co/KEMTBHa8Qk

✔️ @InvestorAmnesia
https://t.co/zFL3H2dk6s

✔️ @mastersinvest
https://t.co/2XxBzxxrYb
Tech focused

✔️ @stratechery
https://t.co/VsNwRStY9C

✔️ @bgurley
https://t.co/NKXGtaB6HQ

✔️ @CBinsights
https://t.co/H77hNp2X5R

✔️ @benedictevans
https://t.co/nyOlasCY1o

✔️ @ARKInvest
https://t.co/VwZuh8aYNw
Tech Deep dives

✔️ @StackInvesting
https://t.co/WQ1yBYzT2m

✔️ @hhhypergrowth
https://t.co/kcLKITRLz1

✔️ @Beth_Kindig
https://t.co/CjhLRdP7Rh

✔️ @SeifelCapital
https://t.co/CXXG5PY0xX

✔️ @borrowed_ideas
https://t.co/yswPHiLeia
Investing Concepts

✔️ @IntrinsicInv
https://t.co/lQOBSNv1Nh

✔️ @JohnHuber72
https://t.co/QslJlfCejm

✔️ Gary Mishuris
https://t.co/9CqfJDNJix

✔️ @GavinSBaker
https://t.co/WTCpxNXvfW

✔️ @NovelInvestor
https://t.co/Wd3E3HxT4D

✔️ @10kdiver
https://t.co/5vjYRdinWV
Investing (Stock Ideas) Articles

✔️ @themotleyfool
https://t.co/4IuGintjK6

✔️ @CatanaCapital
https://t.co/QvNIwRFIZm

✔️ The Good Investors - Singapore
https://t.co/n2sUNyI5MM

✔️ New Academy of Finance
https://t.co/2X8y4jaUDa
Seeking Alpha (most articles open for subscribers only).

✔️ @FromValue
https://t.co/lBCoTv9Pyf

✔️ @andrescardenal
https://t.co/1iDCN57C5p

✔️ Integrator
https://t.co/rdmpWNFnMs

✔️ @EconomyApp
https://t.co/daJxFnp3ie

✔️ Bert Hochfeld
https://t.co/zh6nxNsafF
Substacks

✔️ @BrianFeroldi
https://t.co/u89relRji3

✔️ @richard_chu97
https://t.co/T0cXm0fXbd

✔️ @jaminball
https://t.co/e6nNnOJf3K

✔️ @adventuresinfi
https://t.co/v5fs3jFKmF

✔️ @JonahLupton
https://t.co/uKgYhwDFUe

✔️ @GetBenchmarkCo
https://t.co/HTybVNu5tX

cont...
✔️ @mrjivraj
https://t.co/TWNuSVdy4H

✔️ @chitchatmoney
https://t.co/tPyfYXPdPT

✔️ @reshoftc
https://t.co/L4fwdFfpoQ

✔️ @StockNovice
https://t.co/UXk4nbRH0D

✔️ @InvestmentTalkk
https://t.co/mM2f1rZNLx

✔️ @MazwoodCap
https://t.co/nJkHFVSrtq

✔️ @packyM
https://t.co/ezXi2S7IEm
Very resourceful folks from their work on/off Twitter👏

@DavidGFool @TMFJMo @TMFStoffel @danielsparks @dannyvena @aaronbush100

@saxena_puru @dmuthuk @Gautam__Baid @dhaval_kotecha @SagaPartners @FocusedCompound @LiviamCapital @bluff_capital @Post_Market @BluegrassCap
Podcasts 🎙️ ⬇️

https://t.co/bkLk58VBy1
Of course it's impossible to read every update on so many different websites/blogs, but checking out some of these every week and then rotating your reading/listening should make you a more balanced and well-informed investor.

A big Thank you🙏 to all those authors.
Overall, this is a golden time (and only improving) for quality online resources for learning Investing (or any other topic for that matter).

All one needs to do is explore, select, filter and then focus.

Good Luck. 👍

More from Ram Bhupatiraju

Ram Bhupatiraju
Ram Bhupatiraju
@RamBhupatiraju
On Seeking Alpha, "Integrator" (not sure about Twitter presence) is one of my favorite authors along with
@FromValue
@andrescardenal
@EconomyApp
Bert Hochfeld
👏👏

Few of my fav articles of his.

1⃣ The 5 Elements That Make For An Outstanding

2⃣ On Lessons from Buffett.

-Seek Economic Moats in any investment
-Having an awareness of your circle of competence
-Investing for the ultra long term
-Take advantage of a bargain hiding in plain sight
-Preservation of Capital, Above

3⃣ 5 Common Mistakes In Evaluating High-Growth Companies

-It has already gone up so much.
-Fearing short interest
-Fearing future Competition
-Fearing stock dilution due to secondary offerings
-Fearing current

4⃣ Ways Investors Cheat Themselves Out Of Long-Term Wealth Creators

-This business doesn't make any money!
-Thinking that you're too late
-Stock volatility
-High Valuation
-About Voting rights
-Aversion to 'averaging

5⃣ The 5 Important Rules For Surviving A Major Economic Downturn

-Strong cash reserves
-Low debt levels
-Good cash flow generation
-An absence of secular headwinds
-Transparent and easily understood
TRADING
Ram Bhupatiraju
Ram Bhupatiraju
@RamBhupatiraju
One of the best Investing blogs I recently came across. h/t @StableBread 👏

Five of my fav articles⬇️

@dmuthuk @saxena_puru @Gautam__Baid

1⃣On Moats
Network Effect
Intangible Assets
Switching Cost
Economies of Scale
Low Cost Provider
Toll
Cultural

2⃣Crucial Investment Principles You Need to Have
Capital Appreciation
Buy Low, Hold, Sell High
Recognize/Avoid Spec Bubbles
Ignore Noise
Stock Market=Pendulum
Diversify Your investments. Don't overdo it.
DCA
Understand Share Price Value
LT Tax

3⃣How to Read and Analyze Any 10-K Annual Report

Business Summary
Risk Factors
Selected Financial Data
Management's Discussion and Analysis
Financial Statements and Supplementary Data
Notes to Consolidated Financial

4⃣The Beginner's Guide to Dividend Investing

Dividend Yield
Dividend Growth Rate
Dividend Payout Ratio
Ability to Pay Back Debt
Net Debt to EBITDA Ratio
Return on Equity
Credit

5⃣How to Calculate the Intrinsic Value of a Company Like Warren Buffett

Owners Earnings
Growth Rate
Discount Rate
Calculate Intrinsic Value
Scenario Analysis
Margin of
ALL
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Ram Bhupatiraju
Ram Bhupatiraju
@RamBhupatiraju
Excellent list of "Investing Don'ts" by @NovelInvestor👏 Some solid advice for long-term investors in individual

The List

1⃣ Do not make hasty, emotional decisions about buying and selling stocks.

2⃣ If you are convinced that a company has dynamic growth prospects, do not sell it because it looks temporarily too high.

3⃣ Do not fall in love with stocks to the point where you can no longer be objective in your appraisal of them…

4⃣ Do not concern yourself as much with the market in general as with the outlook for individual stocks…

5⃣ Forget about stock market “tips.”

6⃣ Remember that stocks always look worst at the bottom of a bear mkt (when an air of gloom prevails) and always look best at the top of a Bull mkt (when everybody is optimistic).

7⃣Remember that you’ll seldom if ever buy stocks right at the bottom or sell them right at the top.

8⃣ Do not buy stocks as you might store merchandise on sale (Don't buy stuff you don't like or meet your objectives)…

9⃣ Remember that the public is generally wrong (during periods of over-enthusiasm or over-pessimism)…
ALL
Ram Bhupatiraju
Ram Bhupatiraju
@RamBhupatiraju
Some pretty good Book summaries in here. h/t @mtmdev_ 👏

My fav ones from the list
✔️Poor Charlie's Almanack
✔️Zero to One
✔️The Millionaire Next Door
✔️Surely You're Joking, Mr.

1⃣ Poor Charlie's Almanack (on Charlie Munger).

Having the actual book and referencing it often is the best option, but checking out these tidbits doesn't

2⃣ Zero to One by Peter Thiel.

Great review of an excellent book that's very useful for anyone interested in

3⃣ The Millionaire Next Door by Thomas J. Stanley and William D. Danko.

This is one of the best personal finance books for a good

4⃣ Surely You're Joking, Mr. Feynman! by Richard
ALL
Ram Bhupatiraju
Ram Bhupatiraju
@RamBhupatiraju
The "Financial Terms Dictionary" on @Investopedia is such a great resource to learn or quickly re-check major Financial terms and concepts. One of the most useful investing bookmark pages. 👏

cc: @dmuthuk @Gautam__Baid

Few samples

✔️Business Cycle
https://t.co/E4Ukh94yi3

✔️Business Model
https://t.co/zCe1CIfMCA

✔️Economic

✔️Real Estate Investment Trust (REITs)
https://t.co/yMXlps6rtz

✔️Master Limited Partnership (MLPs)
https://t.co/M3mD37H8x4

✔️Venture

✔️Accounting Equation
https://t.co/Oix0I3wA5j

✔️Quality of
ALL

More from Machine learning

IM POCUS Focus
IM POCUS Focus
@IMPOCUSFocus
A tweetorial on optimal machine settings for B line image acquisition, with a focus on: focal position at pleura, harmonics off, and increased far gain.

Inspired/based on the recent article - https://t.co/vv2xBSZm6N
@cameron_baston @IsaacMatthiasM1

#POCUS #IMPOCUS

1/18

Let's start with some polls
We will stick to low frequency probes here (i.e. curvilinear and phased array - linear has its own purpose for detailed pleural assessment)

Which preset do you prefer for B line assessment?

2/

What depth do you typically set?

3/

After selecting preset and selecting depth, do you ever adjust any other machine settings to optimize B line assessment?

4/

Importantly, there is no right answer to the above questions!

We won't discuss much about preset or probe type. But we will discuss machine settings to optimize B line quality, based on
1) Theory based on physical basis of B lines
2) In vitro study
3) Study in patients

5/
MACHINE LEARNING
Santiago
Santiago
@svpino
The 8-step quick-start guide to learn Machine Learning.

🧵👇

1⃣ Start with Python 🐍

Yes, you can do other languages, but Python is by far the most straightforward option.

👇

2⃣ Get familiar with numpy, pandas, and matplotlib

These three libraries are probably the most common Python libraries you'll have to use every day.

(Even if you don't end up doing machine learning, these libraries are awesome and useful.)

👇

3⃣ Start using notebooks

Look into Jupyter or Google Colab.

Notebooks are essential for data scientists and machine learning practitioners. Most of the code you'll read and write will be in notebooks.

👇

4⃣ Find a problem (already solved)

In my opinion, the best way to start is by working through a problem —especially when you can learn from its solution.

Start with something simple. I usually recommend "Titanic" from Kaggle.

👇
MACHINE LEARNING , STARTING MACHINE LEARNING
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Cory Doctorow #BLM
Cory Doctorow #BLM
@doctorow
We hear a lot about Facebook as a platform for manipulation - using machine learning to bypass our critical faculties and trick us into believing things that are bad for us - but the real show is in Facebook's ability to target, not manipulate.

1/


People who hold disfavored views struggle to find one another and mobilize. To find other people that feel the same way as you and make common cause with them to effect political change, you have to reveal your views and suffer social sanction.

2/

Search allows people who hold these views to find one another. If you have a deep feeling about your gender being nonbinary but don't know the words for it, you can search for communities of people who have those words, join them, and discover who you've been all along.

3/

This is why, in this moment, so many ideas are migrating from the fringe to the center: ideas about racial justice, gender identity, alternatives to market systems, etc. People have harbored these views all along, but have held back on expressing them.

4/

Being able to express yourself in private, among people who share your views, is a prelude to going public and putting your case to the wider world in hopes of effecting change.

5/
MACHINE LEARNING
Pratham Prasoon \U0001f680
Pratham Prasoon 🚀...
@PrasoonPratham
Here's how I got started with my first machine learning project and you can too.
Let's take a look.

(This thread will take from zero to being a hero in machine learning, trust me)

(1 / 22)
🧵👇


Getting started with your first machine learning project might actually much easier than it seems, if I can do it, certainly anyone can.

I did not use:
- Any Math
- An expensive computer
- Complex programming concepts

(2 / 22)

Here's what I did use:

- A free GPU on Google Colab
- Python
- TensorFlow
- Numpy
- Pandas
- Kaggle
- Scikit-Learn
- Google
- StackOverFlow

(3 / 22)

This project was actually a Kaggle challenge based on the MNIST dataset which is a collection images of 70,000 hand written digits.

You can find the dataset here👇
🔗//kaggle.com/c/digit-recognizer

(4 / 22)


Before we go over the code of this project, it is highly reccomended that you complete this free course on YouTube👇

Machine Learning foundations course
🔗//youtu.be/_Z9TRANg4c0

Code👇
🔗//colab.research.google.com/github/PrasoonPratham/Kaggle/blob/main/MNIST.ipynb

(5 / 22)
MACHINE LEARNING
Prashant \U0001f4da
Prashant 📚
@capeandcode
Ever heard of Autoencoders?

The first time I saw a Neural Network with more output neurons than in the hidden layers, I couldn't figure how it would work?!

#DeepLearning #MachineLearning
Here's a little something about them: 🧵👇


Autoencoders are unsupervised neural networks whose architecture you can picture as two funnels connect from the narrow ends.

These networks are primary focus for compression tasks of data in Machine Learning.

We feed them the data so that they can learn the most important features, a smaller representation while keep the integrity of the data.

Later when someone needs, can just take that small representation and recreate the original, just like a zip file.📥

Being unsupervised, they require no labels.
Our inputs and outputs are same and a simple euclidean distance can be used as a loss function for measuring the reconstruction.

Of course, we wouldn't expect a perfect reconstruction.

We can think of an autoencoder having two components, encoder and decoder, represented by the below equations:

We are just trying to minimize the L here. All the backpropagation rules still hold.
MACHINE LEARNING

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@Belposto_korea
The RV and the Redemption Funds.

ALL Exchanged Currencies as well as all Zim Redemption funds will be placed in the accounts they set up in the Quantum Financial System./1

Absolutely none of these funds will be placed in a Bank at the redemption appointment. Bank computers cannot be programmed to transfer Digital Gold Certificates./2

The QFS can and will transplant funds into a bank account as has been explained earlier,/3

so a person can transfer funds to their own bank account but the desirability will become less and less as the banks go into receivership and their customer’s deposits are confiscated to avoid the Bank’s demise./4

Which bank can compete with the QFS when the QFS is free, secure, private, and stable? One of the major problems in the transition will be the use of Debit Cards for merchant purchases. Will VISA or Mastercard be available?/5
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Michael Dearing
Michael Dearing
@mcgd
An irony of facebook's situation.

Sheryl got her MBA at Harvard. One of the most famous cases (Extra Strength Tylenol) in one of the most famous classes (Business History) she took: in 1982, someone put cyanide in Extra Strength Tylenol capsules and killed 7 people in Chicago.

What do you do when someone turns your product into a weapon? When they use the system you built to harm? James Burke, CEO of J&J, was shockingly open with the public, he pulled the product and made significant packaging changes to make product safer (but not tamper-proof).

He over-shared every step along the way re investigation, redesign, stood up as both CEO and human. The reintroduction of new Extra Strength Tylenol succeeded. Burke saved the brand.

But four years later it happened again. A killer put cyanide in the capsules, this time a woman in Yonkers died. Same CEO, Burke, pulled the product again, completely changed the form factor from capsule to caplet and relaunched *again*. It worked *again*. How'd they do that?

Burke (CEO) tapped J&Js goodwill bank account w/ the public. Two big withdrawals from that bank account in four years + 8 dead bodies! But his honesty, openness, humanity (choked up about the deaths more than once), humility kept the goodwill bank balance positive the whole time.
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Noah Smith
Noah Smith
@Noahpinion
1/OK, I should really write another thread about university-centric regional development, because I think people often make some (very understandable) mistakes when thinking about this issue.

2/The biggest myth, I think, is that universities help regions by educating locals as undergraduates.

Skeptics of universities say: "But most of the people who graduate end up leaving."

3/In fact, most of what a university does for a regional economy is NOT about educating local kids.

Educating local kids is good for the nation, but doesn't help a region much.

The way a university helps a region is through

4/Undergraduates usually leave town after graduation.

But university RESEARCH pulls in OTHER smart people from other regions, and they stay there.

Here's a paper showing that this is the main way universities increase a region's human capital:

5/Research also pulls in business investment.

Companies want to partner with university labs, so they can commercialize the technologies the labs produce. So they invest in the labs, and sometimes they even put their offices in the town.
SOCIETY
Aditya Todmal
Aditya Todmal
@AdityaTodmal
The absolute best 15 scanners which experts are using.

Got these scanners from the following accounts:

1. @Pathik_Trader
2. @sanjufunda
3. @sanstocktrader
4. @SouravSenguptaI
5. @Rishikesh_ADX

Share for the benefit of everyone.

Listing all scanners from @Pathik_Trader Sir first.

1. Open

2. 80-20 Reversal Setup


3. Fake

4. Trapping Inside Bar (Positional Setup)
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Robin Berjon
Robin Berjon
@robinberjon
Recently, the @CNIL issued a decision regarding the GDPR compliance of an unknown French adtech company named "Vectaury". It may seem like small fry, but the decision has potential wide-ranging impacts for Google, the IAB framework, and today's adtech. It's thread time! 👇

It's all in French, but if you're up for it you can read:
• Their blog post (lacks the most interesting details): https://t.co/PHkDcOT1hy
• Their high-level legal decision: https://t.co/hwpiEvjodt
• The full notification: https://t.co/QQB7rfynha

I've read it so you needn't!

Vectaury was collecting geolocation data in order to create profiles (eg. people who often go to this or that type of shop) so as to power ad targeting. They operate through embedded SDKs and ad bidding, making them invisible to users.

The @CNIL notes that profiling based off of geolocation presents particular risks since it reveals people's movements and habits. As risky, the processing requires consent — this will be the heart of their assessment.

Interesting point: they justify the decision in part because of how many people COULD be targeted in this way (rather than how many have — though they note that too). Because it's on a phone, and many have phones, it is considered large-scale processing no matter what.
TECH