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Santiago
@svpino 4 years, 4 months ago 634 views

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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.

5. Write a function that finds the largest and smallest number in an unsorted array.

6. Write a function that finds a subarray whose sum is equal to a given value.

7. Write a function that finds the contiguous subarray of a given size with the largest sum.

8. Write a function that, given two arrays, finds the longest common subarray present in both of them.

9. Write a function that, given two arrays, finds the length of the shortest array that contains both input arrays as subarrays.

10. Write a function that, given an array, determines if you can partition it in two separate subarrays such that the sum of elements in both subarrays is the same.

11. Write a function that, given an array, divides it into two subarrays, such as the absolute difference between their sums is minimum.

I'd love to see some answers!

If you want more content on software engineering, machine learning, and adjacent topics, give me a follow. I post threads like this every week. You can enjoy more of this content here: @svpino.

More from Santiago

Santiago
@svpino

I'll blow your mind with a technique you aren't using yet.

Sometimes, you want your system to do exactly the opposite of what your machine learning model thinks you should do.

Let me convince you. ↓

I'm going to start with a nice problem:

Imagine a model that looks at a picture of an electrical transformer and predicts whether it's about to break or not.

Don't worry about how the model does this. We are going to focus on the results instead.

There are 4 possible results for this model:

1. It predicts a bad unit as bad.
2. It predicts a bad unit as good.
3. It predicts a good unit as bad.
4. It predicts a good unit as good.

#2 and #3 are the mistakes the model makes.

Assuming we run 100 units through the model, we can organize the results in a matrix:

• The rows represent the "actual" condition of the transformer.

• The columns represent the "prediction" of the model.

We call this a "Confusion Matrix."

This is how we can read this confusion matrix:

• 60 bad units were predicted as bad.
• 3 bad units were predicted as good.
• 7 good units were predicted as bad.
• 30 good units were predicted as good.

Santiago
@svpino

Many machine learning courses that target developers want you to start with algebra, calculus, probabilities, ML theory, and only then—if you haven't quit already—you may see some code.

I want you to know there's another way.

↓

2. For me, there's no substitute to seeing things working, trying them out myself, hitting a wall, fixing them, seeing the results.

A hands-on approach engages me in a way pages of theory never will.

And I know many of you reading this are wired just like me.

3. I feel that driving a car is a good analogy.

While understanding some basics are necessary to start driving, you don't need to read the entire manual before jumping behind the wheel.

As long as you practice in empty parking lots and backroads, you'll be fine.

4. As you make your way to public roads, you can start incorporating more of the theory that will help you stay safe.

At this point, that theory won't be lost on you: your hours behind the wheel will help you make the necessary connections.

Things will start clicking quick.

5. I've talked to people struggling with derivatives that have no idea why or when they'll become helpful.

I've seen others memorizing what eigenvectors are, or manually transposing matrices because "that's what it takes."

Honestly, for the most part, it's not.

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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.

👇

Santiago
@svpino

Some of the things I've learned in more than 20 years in the tech industry.

You need to hear these.

🧵👇

Listen to more people who don't look like you, don't speak your language, and don't come from the same place you do.

We aren't doing this near enough.

Small habits compound.

No small improvement is too small.

Just aim for something new every day, and you'll be surprised at the end.

Take responsibility.

It doesn't really matter how you feel, I'm sure you could have done better.

Always keep the big picture in mind and never lose the forest for the trees.

Be the person that pulls everyone out of the rabbit holes.

Santiago
@svpino

My recommendations to start with machine learning math:

• Statistics 110: Probability — Harvard University
• Essence of Linear Algebra — 3Blue1Brown
• Multivariate Calculus — Coursera

Links and 3 additional free resources here: https://t.co/fEmpmRKEvJ

If you are looking for more machine learning content, give me a follow and I’ll keep your feed interesting 😉.

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Zuckerberg says FB is in the process of setting up a "new independent body" that users will be able to appeal content takedowns to. Sort of like the "Facebook Supreme Court" idea he previewed earlier this year.

Zuckerberg: "One of my biggest lessons from this year is that when you connect more than 2 billion people, you’re going to see the good and bad of humanity."

This is how Facebook says it's trying to change the engagement pattern on its services. https://t.co/3p0PGc912o

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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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Taking Down an Insider Threat

"I had all of the advantages. I was already inside the network. No one suspected me. But they found my hack, kicked me off the network...

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Could they stop me once I was inside?

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During most of the first morning, I completed onboarding, made introductions, and completed menial tasks.

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...but here are some other things you might not know about our deploys that are very special 🧵

Netlify has a concept of "atomic" deploys- which means a few things:

- You can preview a deploy when you've or someone else has just put in a PR

- You can roll back to ANY previous state, with one click, in milliseconds

- You always know what state your cache is in!

Netlify allows you to cancel a deploy- did you just put in a change, merge it and then realize you've made a terrible mistake? I've never done that. 😬 er...

No worries. You can cancel that deploy with the click of a button.

You can lock a deploy. Let's say you get everything ready for a big release, code review and tests are complete, it's all ready.

You can lock a deploy in a state to get ready for a major release, so that you know exactly what you're releasing and sleep well the night before. 😴

You can even get notifications about locked deploys via email, outgoing webhook, or Slack. Netlify can notify you when a deploy is either locked or unlocked.

$Katrina Leonoudakis \U0001f453 Miyamura Appreciation Club$

Katrina Leonoudakis 👓 ...
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Machine translation can be a wonderful translation tool, but its uses are widely misunderstood.

Let's talk about Google Translate, its current state in the professional translation industry, and why robots are terrible at interpreting culture and context.

Straight to the point: machine translation (MT) is an incredibly helpful tool for translation! But just like any tool, there are specific times and places for it.

You wouldn't use a jackhammer to nail a painting to the wall.

Two factors are at play when determining how useful MT is: language pair and context.

Certain language pairs are better suited for MT. Typically, the more similar the grammar structure, the better the MT will be. Think Spanish <> Portuguese vs. Spanish <> Japanese.

No two MT engines are the same, though! Check out how human professionals ranked their choice of MT engine in a Phrase survey:
https://t.co/yiVPmHnjKv

When it comes to context, the first thing to look at is the type of text you want to translate. Typically, the more technical and straightforward the text, the better a machine will be at working on it.

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#story
This is a story which describes how River Kaveri was brought on earth by Agastya muni. There was a king named Kavera lived in the Brahmagiri hills who prayed to Brahma for a child. He was blessed with a daughter whom he named Kaveri.

Agastya muni married her. A demon, named Shoorapadma, wanted to trouble people so he prevented rain from reaching South India. As a result famine occurred in South India.
Agastya Muni who came that way was very sad seeing this. He started to pray Mahadeva for a solution.

Shiva gave him small amount of Ganga water in his Kamandalu (small pot) and said wherever you spill this water the river will flow from there. Agastya Muni travelled lot of places to find a suitable place to pour water. Feeling tired he kept his Kamandalu and took rest.

At that time Ganesha took a form of crow and perched on the Kamadalu and made a hole that water began to flow as river Kaveri. This place is now called as Talakaveri (Karnataka), located in the Brahmagiri hill.

Tala Kaveri has temple for Agastheeswara, which denotes the story between Kaveri and Agasthya muni. Kaveri is a part of Ganga, thus, also called Dakshina Ganga.
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Anshul Pandey
@Anshulspiritual

SHAKTA DHARMA AND THEIR ACHARYAS

Śhākta or Shakti or Devi pooja is not a new upasana. It is being carried out right from the time of Vedic period. Puran's tell us that Rishi Vashishth would worship Tara devi. Parshuram ji worshipped Tripura devi,

Agastya learned the secrets of Shri Vidya from Vishnu ji in Hayagriva avtaar. Bhagwan Ram, Laxman and Krishna too learned the tantrik vidya. Even Rig Ved 7.103.5 Sayan Bhasya also mentions about Śhākta/शाक्त(शाक्तस्येव शक्तिमतः).

Then we find that in the Harrappan excavations many figurines depicting Shakti were found. So in that age too, which was supposedly an urban city shakti was being worshipped. So naturally this tradition would be prevalent in rural areas too.

It is wrong to say that shakti puja originated from Bengal although it was popular there. Matsyendranath received this vidya from Maheshwari herself in Kamrup. We know that Shakti pooja is practised all over India.

Not much is known about the Śhākta saints in other parts of India in the middle ages.

Adi Shankaracharya wrote Pramanech saar named book on tantra and Anand lahri book on Devi strotras. Then there were Acharya Shankar, Bhaskar Rai, Laxman, Deshikendra, Raghav Bhatt, Krishnand,