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Saved by @ankitsrihbti

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.
Why not your favorite IDE running on your computer?

That also works, but I'd recommend you get familiar with notebooks from day 1 (@code supports Jupyter notebooks!)

If/when you need a GPU, Google Colab has them for free.
3rd item: You need a way to load and manipulate data.

Pandas is Python's most popular library to do this.

You can go through this tutorial in about 4 hours: https://t.co/RMJJSAVPwT.
Why the big deal with a library to handle data?

Most of the work is just that.

This sounds boring, but I promise it isn't. I can also tell you that it's one of the places where you'll get to show off your creativity.
Visualizing results is number 4 in the list.

Many people skip this step. That's a mistake.

A couple of popular options for you:

• Matplotlib
• Seaborn

Communication is one of the most powerful traits you could build. These libraries will help you do that.
Another 4-hour tutorial: https://t.co/V0ya8kLeCW

This will give you everything you need to start with Seaborn.
At this point, you should be ready to start with specific machine learning content.

Many people go right away and start a course.

Here is a different way: Learn about one algorithm that could solve a problem for you.

This will motivate you to dive deeper.
As a developer, you already have experience learning new things.

• You find a problem.
• You look for a solution.
• You learn about it.
• You implement it.

I want you to try the same here.

Algorithm recommendation: Learn about Decision Trees to start.
Listen up: you don't need to go and become an expert on Decision Trees.

At this point:

• You don't need to worry about the math.
• You don't need to understand the full theory.

All of that can come later.

For now: How can you use Decision Trees? How are they helpful?
A couple of recommendations to get into Decision Trees:

• A tutorial with a lot of code: https://t.co/xz1yUaDxF6

• A video that builds a Decision Tree from scratch: https://t.co/tKtUpO1K3l
It's time for a machine learning introductory course.

(If you looked into Decision Trees already, great! This course will be easy.)

Starting from scratch, in 3 hours, you can go through this: https://t.co/qQXBcdvnsj.
This course puts together everything we just discussed.

It even takes you through a simple problem and helps you solve it!

Good news: The course focuses on building and doesn't worry too much about math or theory.

(These are important, but not now.)
Final item from the list: You need a project.

One of the best problems to start: "Titanic - Machine Learning from Disaster."

You can find it here: https://t.co/eQzuGeePe2.
Optionally, you can take a look at this tutorial on how to solve the Titanic challenge:

https://t.co/DTA0B3GncE

A step-by-step guide that will help you get your first problem done!
Let's recap:

1. You need experience with Python
2. Learn Google Colab
3. Pandas for data
4. Seaborn for visualizations
5. Decision Trees is a good start
6. Finish "Intro to Machine Learning."
7. Solve the Titanic challenge

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Santiago
@svpino
An introduction to one of the the most basic structures used in machine learning: a tensor.

🧵👇

Tensors are the data structure used by machine learning systems, and getting to know them is an essential skill you should build early on.

A tensor is a container for numerical data. It is the way we store the information that we'll use within our system.

(2 / 16)

Three primary attributes define a tensor:

▫️ Its rank
▫️ Its shape
▫️ Its data type

(3 / 16)

The rank of a tensor refers to the tensor's number of axes.

Examples:

▫️ The rank of a matrix is 2 because it has two axes.
▫️ The rank of a vector is 1 because it has a single axis.

(4 / 16)

The shape of a tensor describes the number of dimensions along each axis.

Example:

▫️ A square matrix may have (3, 3) dimensions.
▫️ A tensor of rank 3 may have (2, 5, 7) dimensions.

(5 / 16)
MACHINE LEARNING , TENSOR BASICS
Santiago
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@svpino
20 machine learning questions that will make you think.

(Cool questions. Not the regular, introductory stuff that you find everywhere.)

🧵👇

1. Why is it important to introduce non-linearities in a neural network?

2. What are the differences between a multi-class classification problem and a multi-label classification problem?

3. Why does the use of Dropout work as a regularizer?

👇

4. Why you shouldn't use a softmax output activation function in a multi-label classification problem when using a one-hot-encoded target?

5. Does the use of Dropout in your model slow down or speed up the training process? Why?

👇

6. In a Linear or Logistic Regression problem, do all Gradient Descent algorithms lead to the same model, provided you let them run long enough?

7. Explain the difference between Batch Gradient Descent, Stochastic Gradient Descent, and Mini-batch Gradient Descent.

👇

8. What are the advantages of Convolution Neural Networks (CNN) over a fully connected network for image classification?

9. What are the advantages of Recurrent Neural Networks (RNN) over a fully connected network when working with text data?

👇
ALL , MACHINE LEARNING
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Santiago
Santiago
@svpino
11 short programming problems to stretch your imagination and make sure you are staying on your toes.

(Starting with the simple ones, they get more fun as you move towards the end.)

🧵👇

1. Write a function that reverses an array in place.

In other words, the function should not use an auxiliary array to do the work.

2. Write a function that finds the missing number in an unsorted array containing every one of the other 99 numbers ranging from 1 to 100.

3. Write a function that finds the duplicate number in an unsorted array containing every number from 1 to 100.

Only one of the numbers will appear twice.

4. Write a function that removes every duplicate value in an array.

There could be more than one value duplicated. You should remove all of them leaving a single copy of the value.
TECH
Santiago
Santiago
@svpino
A surprising situation.

A machine learning model predicting 3 classes ends up with these results:

• Class A: 90% accuracy
• Class B: 80% accuracy
• Class C: 70% accuracy

Class C seems to be the worst-performing.

But you know already that I'll say it isn't. ↓

Here is the correct answer: We don't know yet which class is the worst.

This is important to understand, so keep reading.

Many people make this same mistake every day and try to fix things that ain't broken.

We are missing something, so let's go and get it.

How about if we ask a friend to look at the dataset manually?

Let's say these are the results of our friend doing the job:

• Class A: 95% accuracy
• Class B: 100% accuracy
• Class C: 71% accuracy

Do you see what just happened?

The model is actually really accurate when predicting Class C! 70% versus 71% when done by a human.

Class B, however, is a disaster: 80% versus 100% when done manually.

Class B seems to be the worse performing class!

The work that our friend did is called a "baseline."

Without having it, it's hard to determine how good are the results of a model.

I've seen tons of money down a drain just because teams didn't create a baseline beforehand.

But now, that won't happen to you 😉.
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Santiago
Santiago
@svpino
10 machine learning YouTube videos.

On libraries, algorithms, and tools.

(If you want to start with machine learning, having a comprehensive set of hands-on tutorials you can always refer to is fundamental.)

🧵👇

1⃣ Notebooks are a fantastic way to code, experiment, and communicate your results.

Take a look at @CoreyMSchafer's fantastic 30-minute tutorial on Jupyter Notebooks.

https://t.co/HqE9yt8TkB


2⃣ The Pandas library is the gold-standard to manipulate structured data.

Check out @joejamesusa's "Pandas Tutorial. Intro to DataFrames."

https://t.co/aOLh0dcGF5


3⃣ Data visualization is key for anyone practicing machine learning.

Check out @blondiebytes's "Learn Matplotlib in 6 minutes" tutorial.

https://t.co/QxjsODI1HB


4⃣ Another trendy data visualization library is Seaborn.

@NewThinkTank put together "Seaborn Tutorial 2020," which I highly recommend.

https://t.co/eAU5NBucbm
MACHINE LEARNING

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श्रीमाली हितेश अवस्थी ...
@HiteshAwasthi89
#Thread
An interesting story of Kamala Devi hazarika for all Sanatanis...🙏

A Xtian missionary was sent to Assam for the promotion of religion. His name was Cruz. He came across to one the boys from an influential family in Assam to teach him English.
@noconversion

Cont 👇


The p@stor slowly began to study the house and he learned that the boy's grandmother was the most influential person in the house. So he thought 'Corrupting the grandmother's mind can make the whole family Xtian as well as the whole village.

Cont 👇


The p@stor began to tell Grandma the stories of how J€$u$ cured leprosy of lepers, how He gave sight to the blind, etc..But after listening to him, the strong Sanatani grandmother said. A stone turned into a living woman (Ahalya) for our Rama when he touched the stone.

Cont 👇


She spoke of Rama setu where stones floated in sea just by writing his name on the stones and that they are still floating today.
The p@stor continued his efforts but all his tricks went in vain.

Cont 👇


One day he had brought a cake from the church and he thought of offering it to grandmother but he was doubtful that she would eat it. But contrary to his expectation, she took the cake and ate it.

Cont 👇
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\u0938\u093e \u0935\u093f\u0926\u094d\u092f\u093e \u092f\u093e \u0935\u093f\u092e\u0941\u0915\u094d\u0924\u092f\u0947
सा विद्या या विमुक्तये...
@raghav_aanya
कुंडली में 12 भाव होते हैं। कैसे ज्योतिष द्वारा रोग के आंकलन करते समय कुंडली के विभिन्न भावों से गणना करते हैं आज इस पर चर्चा करेंगे।
कुण्डली को कालपुरुष की संज्ञा देकर इसमें शरीर के अंगों को स्थापित कर उनसे रोग, रोगेश, रोग को बढ़ाने घटाने वाले ग्रह


रोग की स्थिति में उत्प्रेरक का कार्य करने वाले ग्रह, आयुर्वेदिक/ऐलोपैथी/होमियोपैथी में से कौन कारगर होगा इसका आँकलन, रक्त विकार, रक्त और आपरेशन की स्थिति, कौन सा आंतरिक या बाहरी अंग प्रभावित होगा इत्यादि गणना करने में कुंडली का प्रयोग किया जाता है।


मेडिकल ज्योतिष में आज के समय में Dr. K. S. Charak का नाम निर्विवाद रूप से प्रथम स्थान रखता है। उनकी लिखी कई पुस्तकें आज इस क्षेत्र में नए ज्योतिषों का मार्गदर्शन कर रही हैं।
प्रथम भाव -
इस भाव से हम व्यक्ति की रोगप्रतिरोधक क्षमता, सिर, मष्तिस्क का विचार करते हैं।


द्वितीय भाव-
दाहिना नेत्र, मुख, वाणी, नाक, गर्दन व गले के ऊपरी भाग का विचार होता है।
तृतीय भाव-
अस्थि, गला,कान, हाथ, कंधे व छाती के आंतरिक अंगों का शुरुआती भाग इत्यादि।

चतुर्थ भाव- छाती व इसके आंतरिक अंग, जातक की मानसिक स्थिति/प्रकृति, स्तन आदि की गणना की जाती है


पंचम भाव-
जातक की बुद्धि व उसकी तीव्रता,पीठ, पसलियां,पेट, हृदय की स्थिति आंकलन में प्रयोग होता है।

षष्ठ भाव-
रोग भाव कहा जाता है। कुंडली मे इसके तत्कालिक भाव स्वामी, कालपुरुष कुंडली के स्वामी, दृष्टि संबंध, रोगेश की स्थिति, रोगेश के नक्षत्र औऱ रोगेश व भाव की डिग्री इत्यादि।
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@OrdersofM
https://t.co/6cRR2B3jBE
Viruses and other pathogens are often studied as stand-alone entities, despite that, in nature, they mostly live in multispecies associations called biofilms—both externally and within the host.

https://t.co/FBfXhUrH5d


Microorganisms in biofilms are enclosed by an extracellular matrix that confers protection and improves survival. Previous studies have shown that viruses can secondarily colonize preexisting biofilms, and viral biofilms have also been described.


...we raise the perspective that CoVs can persistently infect bats due to their association with biofilm structures. This phenomenon potentially provides an optimal environment for nonpathogenic & well-adapted viruses to interact with the host, as well as for viral recombination.


Biofilms can also enhance virion viability in extracellular environments, such as on fomites and in aquatic sediments, allowing viral persistence and dissemination.
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Learn Python With Rune
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@PythonWithRune
9 Python resources that will fast-track your learning

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1️⃣ Introduction to Python Programming

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✔️ Boost your hirability through innovative, independent learning.

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✔️ Introduction to computer science
✔️ A tool to solve real-world analytical problems
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professorstam.eth
professorstam.eth
@ProfessorStam
I worked in bank liquidity and treasury for the better part of the last decade, and there is one very interesting risk factor from the SVB collapse that I do not think we have ever witnessed before in modern finance, a 🧵:

First, some context. Following the 2008 financial crisis where a massive driver of stress was caused by low quality assets littering the balance sheets of massive institutions, the regulators sought to create a framework to ensure all banks were verifiably sound.

This meant forcing Federally registered banks to conform to capital and liquidity ratios. If they did not comply, they would not be allowed to issue dividends or buy back stocks, hurting the value of their enterprise.

There was the introduction of the concept of RWA, or risk weighted assets. A simple way to think of these ratios is, the riskier your asset base on a weighted basis, the more high quality capital (think cash) you would need to hold to stay in compliance.

Not only were banks required to regularly be in compliance with these ratios as a going concern, but needed to prove they could maintain certain limits when met with a time of stress across a number of incrementally adverse scenarios.
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Jaya_Upadhyaya
Jaya_Upadhyaya
@Jayalko1
SRISAILAM: KASHI OF THE SOUTH (AP)
#andhratemples

The divine abode of Mallikarjuna Swamy (Jyotirlinga) and Devi Brahmaramba (Shaktipeeth).

When Ganesha was married before Kartikeya, he left in anger to Kraunch mountain. Shiva and Parvati also followed him there.


Shiva assumed the form of Jyotirlinga and resided on the mountain by the name of Mallikarjuna. Mallika means Parvati while Arjuna is another name of Shiva
It is also said that once, a princess Chandravathi, saw a cow shedding milk on a rock resembling a shivlingam.
@DubeyYash1911


She started praying to the lingam daily and used to offer jasmine (mallika pushpam) daily. Pleased Shiva appeared before her and agreed to wear jasmine garland (mallika pushpmala) on his head permanently. Since then, Shiva became known as Mallikarjun Swamy.


At this place, Shakti took the form of Bhramaram (bee) to kill Arunasur and settled as Bhramaramba Devi. The place is a Shakti Peeth as the neck portion of Devi Sati fell here.

It is said that by merely seeing the hill, one is emancipated from all his sins and worries.
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Anu Satheesh \U0001f1ee\U0001f1f3
Anu Satheesh 🇮🇳...
@AnuSatheesh5
Yoga Ramar Temple
#Nedungunam
#TamilNaduTemples 🚩

Yoga Ramar Temple is located near Thiruvannamalai. Shri Rama is seated with eyes closed, without any weapons. Mata Sita  pointing to the feet of Rama telling that  everyone is safe at his feet. Lakshmana standing near Shri Rama


Hanuman is seen chanting Vedas obediently sitting before Shri Rama.

Sthala Puranam says that, Sukabrahma Maharishi had been doing Tapasya here, for the darshan of Sri Rama. Prabhu Shri Ram, pleased with his tapasya, came here after Rama Ravana yudham. Since Rama was returning


after the war, he did not have any weapons with him.

Another gopuram called Kili Gopuram is there for Sukabrahma Maharishi. There is a hill nearby called Dheergachala. According to Sthala puranam, Sri Padham of Prabhu Rama are found on the top of the hill


It is said that this is the place where Shri Rama gave darshan to Suka Maharishi. Nedumgunam means which shows all qualities of Shri Rama who is Maryadha purushottam. Shri Ramanavami is very famous here.

Jai Sri Ram
🙏🕉🙏
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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
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அஸ்தினாபுரத்து அரசி👸...
@SivaRoobini555
#தினம்_ஒரு_திருவாசகம்
தொல்லை இரும்பிறவிச் சூழும் தளை நீக்கி
அல்லல் அறுத்து ஆனந்தம் ஆக்கியதே – எல்லை
மருவா நெறியளிக்கும் வாதவூர் எங்கோன்
திருவாசகம் என்னும் தேன்

பொருள்:
1.எப்போது ஆரம்பித்தது என அறியப்படமுடியாத தொலை காலமாக (தொல்லை)

2. இருந்து வரும் (இரும்)


3.பிறவிப் பயணத்திலே ஆழ்த்துகின்ற (பிறவி சூழும்)

4.அறியாமையாகிய இடரை (தளை)

5.அகற்றி (நீக்கி),

6.அதன் விளைவால் சுகதுக்கமெனும் துயரங்கள் விலக (அல்லல் அறுத்து),

7.முழுநிறைவாய்த் தன்னுளே இறைவனை உணர்த்துவதே (ஆனந்த மாக்கியதே),

8.பிறந்து இறக்கும் காலவெளிகளில் (எல்லை)

9.பிணைக்காமல் (மருவா)

10.காக்கும் மெய்யறிவினைத் தருகின்ற (நெறியளிக்கும்),

11.என் தலைவனான மாணிக்க வாசகரின் (வாதவூரெங்கோன்)

12.திருவாசகம் எனும் தேன் (திருவா சகமென்னுந் தேன்)

முதல்வரி: பிறவி என்பது முன்வினை விதையால் முளைப்பதோர் பெருமரம். அந்த ‘முன்வினை’ எங்கு ஆரம்பித்தது எனச் சொல்ல இயலாது. ஆனால் ‘அறியாமை’ ஒன்றே ஆசைக்கும்,, அச்சத்துக்கும் காரணம் என்பதால், அவையே வினைகளை விளைவிப்பன என்பதால், தொடர்ந்து வரும் பிறவிகளுக்கு, ‘அறியாமையே’ காரணம்

அறியாமைக்கு ஆரம்பம் கிடையாது. நமக்கு ஒரு பொருளைப் பற்றிய அறிவு எப்போதிருந்து இல்லை? அதைச் சொல்ல முடியாது. அதனாலேதான் முதலடியில், ஆரம்பமில்லாத அஞ்ஞானத்தை பிறவிகளுக்குக் காரணமாகச் சொல்லியது. ஆனால் அறியாமை, அறிவின் எழுச்சியால், அப்போதே முடிந்து விடும்.
ALL
Shaan Puri
Shaan Puri
@ShaanVP
If you're a college student who wants to pay off all your loans... here's an idea for you:

It takes ~$5k to start and will make ~$30k a year of profit

It won't get you rich, it'll pay for college.

(..and will teach them more about business than they’ll learn in school)

The idea isn’t sexy. But it works:

**Plastic Moving Bin Rentals**

Everyone knows moving sucks. The worst part is being stuck with 400 cardboard boxes at the end of your move.

Instead - @benmlevy told me about Gorilla Bins. They dropoff plastic moving bins, & pickem up later.


Let’s break it down. Our goal is to pay for college (~$30k profit per year).

To do that, I think we’ll need $50k in revenue.

The avg move (a 2 bedroom apartment) is $180

To hit our goal, we need do ~5.5 moves per week

COSTS?

How many bins do we need to buy up front?

5.5 moves a week x 50 bins = you need 275 bins. Let’s round up to 300 to be safe.

Ok let’s hop over to @uline to see how much these bins cost

Bingo. Bins cost about $15 a piece.

$15 x 300 bins = $4,500 initial startup costs.

Time to beg your parents or a rich aunt to lend you money to get the biz rolling (...or just take $5k of student loan money and invest it here…)
FINANCE