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Santiago
@svpino 4 years, 7 months ago 743 views

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The two main machine learning techniques used in the industry today:

1. Gradient Boosted Trees
2. Deep Learning

Focus your time learning Scikit-Learn, XGBoost, and a Deep Learning library like Keras or PyTorch and you'll get the most for your time.

If you need to deal with structured data: Scikit-Learn + XGBoost.

If you need to deal with unstructured data (perceptual tasks): Keras or PyTorch.

Of course, there are many more techniques that will be helpful, but if you focus on these you'll be maximizing your ability to deliver value in the short term.

More from 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 😉.

Santiago
@svpino

12 machine learning YouTube videos.

On libraries, algorithms, tools, and theory.

↓

1. Jupyter Notebooks: https://t.co/HqE9yt8TkB

2. Pandas: https://t.co/aOLh0dcGF5

3. Matplotlib: https://t.co/tKADpmihkh

4. Seaborn: https://t.co/s8EUxh6x1f

5. Numpy: https://t.co/pJoc0Lfjwm

6. Decision Trees: https://t.co/tKtUpO1K3l

7. Neural Networks: https://t.co/bc7emyjc9q

8. Scikit-Learn: https://t.co/LrKG7cMxRq

9. TensorFlow: https://t.co/fhO6T9sblU

10. PyTorch: https://t.co/5w9mJxijdd

11. Essense of Linear Algebra: https://t.co/o3kOnxl90i

12. Essense of Calculus: https://t.co/rfo7v0cpR4

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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)

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 😉.

Santiago
@svpino

Some of my machine learning books.

Hands-On Machine Learning from @aureliengeron and Deep Learning with Python from @fchollet.

More from Ds

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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Santiago
@svpino

I sat next to one of the smartest, most successful software engineers in the country for over 10 years.

Here's what I learned.

Fast is 10 times better than good.

9 out of 10 times, a "good enough" solution is all you need to unlock time, money, and attention.

Focus relentlessly on being first. Then take the time to be right.

Fast, then right.

Ship more frequently.

The faster you show your work to your users, the faster you'll hear their feedback, you'll adapt, and you'll ship again.

A question you should ask every day:

What can I do to ship this one day before planned?

Technical debt is a good thing.

Everyone hates technical debt. I think they don't know how to take advantage of it.

When used appropriately, technical debt means working on what truly matters and deferring anything that can wait.

No debt ⟶ You waited too long.

Ask, don't think.

People burn their time every day instead of asking for help.

You don't get extra points for working harder, especially when a little help will make you faster.

Time is your most valuable resource. Don't waste it.

Sahil Sharma
@sahil_vi

@dixit_37 Yup, autocorrect. 😅

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.

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The Ife Primary Education Research Project (1970-1983).

aka

The Ife 6-Year Primary Project.

In 1970, as the Director of the Institute of Education of the then University of Ife (now Obafemi Awolowo University, Ile-Ife), later Dean Faculty of Education, Prof. Babs Fafunwa & his team embarked on one of the most groundbreaking research projects in education for Yorubaland.

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The project was based on the premise that:

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Jonathan Ware
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Rhino Barges

One of the dullest, coolest, more bizarre and fascinating pieces of kit used in Normandy.

Which NO ONE REALLY CARES ABOUT.

BUT I DO AND YOU SHOULD TOO.
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#WW2 #SWW #History

Planning for Overlord and Neptune had a serious snag, how to get troops from LSTs onto the beach as simply ramming them onto the beaches and dropping the ramp was known to damage the exceptionally vulnerable LSTs and felt to be unsustainable in the mid to long term. /2

LSTs were essential in sustaining Overlord's progress and were a subject of major headaches in the planning phase, and a real subject of friction when it came to launching additional amphibious operations such as Dragoon.

A single LSTs loss represented a capability nick. /3

So, logic dictated, we don't really want these remarkable but rare and highly valuable vessels constantly doing beach landings, we want something to act as a medium between ship to shore, and in came the (mostly) American designed Rhino. /4

I fucking love Rhinos.

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Graceful lines of pure industrial pedigree.

Modular.

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श्रीमाली हितेश अवस्थी...
@HiteshAwasthi89

Sri Devi Karumariamman mandir, Chennai, Tamilnadu

Sri Devi Karumariamman mandir is in Thiruverkadu, a suburb of Chennai. It is said that God Muruga came here and obtained the 'Vel' (spear) from His mother, Goddess Karumari (an avatar of Parvathi) 1/n

to fight the demon Suran and hence this place was called as 'Vel kadu' and became as Verkadu. As per legend Devi Karumariamman once disguised as a soothsayer visited Bhagwan Surya, the Sun God, to predict His future. 2/n

Not realising that the soothsayer is none other than Sakthi Matha, Surya ignored Her. Angered by his indifference, Devi Karumariamman immediately retreated. Bhagwan Surya lost His glory and the earth plunged into darkness. 3/n

Bhagwan Surya then realised His folly and pleaded forgiveness from Devi Karumariamman. In order to pacify mother Karumariamman, Suryadev said that His rays would fall on Her directly twice in a year and touch her feet. (in the month of Panguni (March- April) & during (Sep - Oct)

Mother Karumari Amman is worshipped here in two forms.A swayambu (self manifested) with only head visible above the ground and another one in a graceful sitting posture with all Parasakthi features,with four arms holding skull, sword, trishul, udukkai (damru). 5/n

Jaya_Upadhyaya
@Jayalko1

KANIPAKAM VINAYAKA, CHITOOR (AP)
#bharatmandir

Kani means wetland and Pakam means flow of water into wetland.
Kanipakam Vinayaka is swayambhu (self-manifested). The murti is in a well which is always full of water.

Once, there were three brothers. Each one had a handicap- Dumb, Deaf and Blind. They had a small piece of land for livelihood. For their field, they drew water from a well. One day, they found that the well had dried up so one of them started digging in the well.

His tool hit something and blood oozed out. They found a swayambhu murti of Ganesha here.
Villagers started offering coconut water which overflew into a channel. Hence the name Kanipakam.

The murti is still growing in size. At present, we see the knees and the abdomen only. The Kavacham (Armour) offered to Vinayaka 50 years ago doesn’t fit today.
Vinayaka is believed to be the upholder of truth. So people come here and swear before him to prove their innocence.

SK
@sk_diary1

Kolaru Pathigam-Thevaram hymn composed by ThiruGnana Sambandar- #Thread

In Tamil Kol means planets,Aru means cut- set of songs in Kolaru Pathigam addresses all Navagrahas& last 2 lines of every song with end a plea to Bhagwan Shiva to reduce/erase the ill effects of Navagrahas

கோளறு பதிகம் - This pathigam was sung by Thirugnana Sambandar at Thirumaraikadu Kshetram -Vedaranyam,Tamilnadu

Thirugnana Sambandar & Appar(Thirunavukkarasar) travelled together to various Shiva Alayam to spread shivam & bhakti among people.They both reached Thirumaraikadu.

Thirumaraikadu(Vedaranyam) -
Appar & Sambandar were asked to enter the temple through side entrance.The main door was locked by Vedas many years ago.Appar&Sambandar sang devotional hymns praising Shiva, after which the gates opened & closed.After which main door opened for all.

After darshan of Bhagwan Shiva at Thirumaraikkadu,Sambandar received a message to travel to Madurai.
During that time, Samanam was on the rise in the Pandya Kingdom.The Pandya King converted to Samanam.The Queen Mangaiyarkkarasi was a staunch Shiva devotee and was upset.

Kularchirai Nayanar ,Chief Minister of Pandya kingdom was in agony by the turn of events.Queen requested Kulachirai Nayanar to escort Thiru gnana Sambandar to Madurai.Kularchirai Nayanar met Thiru gnana Sambandar at Thirumaraikkadu & requested him to visit Madurai.