BC MACHINE LEARNING

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Santiago
@svpino 5 years, 5 months ago 1040 views

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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

5⃣ Numpy is another Python library that you will use every single day.

@keithgalli's "Complete Python NumPy Tutorial" is a great start.

https://t.co/Xg0YbuR8fz

6⃣ One of the most basic algorithms that you can learn is Decision Trees.

Watch @random_forests' video where he builds a decision tree from scratch:

https://t.co/tKtUpO1K3l

7⃣ It's hard to talk about machine learning without touching on neural networks.

Probably the best video out there that explains how neural networks work is @3blue1brown's:

https://t.co/OMJHiG7PIu

8⃣ Scikit-Learn is one of the most popular machine learning libraries out there.

@simplilearn's "Scikit-Learn Tutorial" is a great place to start.

https://t.co/efd1kmz07c

9⃣ TensorFlow is the most popular deep learning library that's currently used in the industry.

Here is a massive 7-hour tutorial of TensorFlow 2.0 produced by @freeCodeCamp.

https://t.co/BYUoAQJEeu

🔟 Finally, a great way to start getting familiar with machine learning is the bite-sized recipes published by Google.

This series is worth every minute.

Playlist: https://t.co/xDqhmNQoWg

If you are looking for real-life, hands-on information related to machine learning, follow me.

✌️

If you have questions or suggestions about topics you'd like to hear about, let me know.

More from Santiago

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

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

My recommendation to start learning how to deal with structured data: Kaggle's Pandas Tutorial.

• Creating, Reading, Writing
• Indexing, Selecting, Assigning
• Summary Functions, Maps
• Grouping, Sorting
• Data Types, Missing Values
• Renaming, Combining

100% Python 🐍.

Santiago
@svpino

Here is a simple example of a machine learning model.

I put it together a long time ago, and it was very helpful! I sliced it apart a thousand times until things started to make sense.

It's TensorFlow and Keras.

If you are starting out, this may be a good puzzle to solve.

The goal of this model is to learn to multiply one-digit

It is a good example of coding, what is the model?
— Freddy Rojas Cama (@freddyrojascama) February 1, 2021

Santiago
@svpino

A topic that comes up in every interview.

Bias, variance, and their relationship with machine learning algorithms. One of the most basic concepts that you have to know by heart.

Here is a simple summary that you will easily remember.

↓

Every machine learning algorithm deals with 3 types of errors:

1. Bias error
2. Variance error
3. Irreducible error

There's nothing we can do about #3.

Let's focus on the other two.

↓ 1/5

"Bias" refers to the assumptions the model makes to simplify the process of finding answers.

The more assumptions it makes, the more biased the model is.

"Variance" refers to how much the answers given by the model will change if we use different training data.

If the answers stay the same regardless of the data, the model has low variance.

Often, linear models are high-bias, and nonlinear models are low-bias.

Example low-bias algorithms:
• Decision Trees
• SVN
• kNN

Example high-bias algorithms:
• Linear Regression
• Logistic Regression

More from Machine learning

Kieran Snyder
@KieranSnyder

1 There's a chasm between an NLP technology that works well in the research lab and something that works for applications that real people use. This was eye-opening when I started my career, and every time I talk to an NLP engineer at @textio, it continues to strike me even now.

2 Research conditions are theoretical and/or idealized. A huge problem for so-called NLP or AI startups with highly credentialed academic founders is that they bring limited knowledge of what it takes to build real products outside the lab.

3 A product is ultimately a thing that people pay for - not just cool technology or user experience. But I’m not even talking about knowledge gaps in go-to-market work. I'm talking purely technical gaps: how you go from science project to performant + delightful user experience.

4 Most commoditized NLP packages solve well-understood problems in standard ways that sacrifice either precision or performance. In a research lab, this is not usually a hard trade-off; in general, no one is using what you make, so performance is less important than precision.

5 In software, when you’re making something for real people to use, these tradeoffs are a big deal. Especially if you’re asking those people to pay for what you’ve made (can’t get away from that pesky GTM thinking). They expect quality, which includes precision AND performance.

Pratham Prasoon
@PrasoonPratham

Machine Learning for the Web developer in 2021.

The beginner's guide.

🧵👇

I started machine learning as a web developer, if I can do it then anyone can.

This carefully curated thread will give you key insights into my journey and how you can make this transition, seamlessly.

(2 / 14)

"Machine learning is not what you think it is"

One of the main reasons why people find it difficult to get started with machine learning is because of the lack of information, and rightfully so.

(3 / 14)

Machine learning as a concept has existed since the 1950s, but has only become popular in recent years because of the exponential rise of advancements in computer hardware.

(4 / 14)

In short, it because of the sudden rise of this technology ,which was previously unknown to the general public, that there is a lot of misinformation around it.

(5 / 14)

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$Pratham Prasoon \U0001f680$

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)

Anson Horton
@AnsonHorton

1/ It's probably not the first thing you think of, but when we started .NET (COM+) in the late 90s, C# didn't exist yet. We were working on it at the same time as the CLR and the framework. So, you might wonder, what language was being used to generate IL and write the BCL?

2/ The answer is a language that we called SMC that Peter Kukol wrote the compiler for. Peter is a flat out amazing engineer and wrote the core parts of the compiler in just a few days. This unblocked the framework team, allowed vetting the runtime and interpreter, etc.

3/ SMC was a trimmed down C++ variant and the compiler was written in itself (i.e. SMC). It didn't support things like destructors, multiple inheritance, virtual base classes, etc. But, overall it enabled progress that would have otherwise been stalled.

4/ It did introduce a problem for the C# language and compiler team though. Every day more and more code was written in SMC, a language that we did not intend to ship externally. Designing a new language is hard (well, at least, a general purpose one that becomes popular).

5/ So there was a constant balancing act between laying enough of the foundation of the language and the C# compiler to replace SMC and making sure that the design lived up to the goals and ideals the team was striving for. If we waited too long to adopt C#,

$Unknown \U0001f464$

Unknown 👤
@console_404

10 PYTHON 🐍 libraries for machine learning.

Retweets are appreciated.
[ Thread ]

1. NumPy (Numerical Python)

- The most powerful feature of NumPy is the n-dimensional array.

- It contains basic linear algebra functions, Fourier transforms, and tools for integration with other low-level languages.

Ref: https://t.co/XY13ILXwSN

2. SciPy (Scientific Python)

- SciPy is built on NumPy.

- It is one of the most useful libraries for a variety of high-level science and engineering modules like discrete Fourier transform, Linear Algebra, Optimization, and Sparse matrices.

Ref: https://t.co/ALTFqM2VUo

3. Matplotlib

- Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.

- You can also use Latex commands to add math to your plot.

- Matplotlib makes hard things possible.

Ref: https://t.co/zodOo2WzGx

4. Pandas

- Pandas is for structured data operations and manipulations.

- It is extensively used for data munging and preparation.

- Pandas were added relatively recently to Python and have been instrumental in boosting Python’s usage.

Ref: https://t.co/IFzikVHht4

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Pegasus of Dharma
@HarduttSuhas

The BATTLE OF PAVAN KHIND (13 July 1660)

300 MARATHAS against 10000+ ADIL SHAHI TROOPS

A Sparta style last man stand at a mountain pass which ensured Shivaji Maharaj's safety.

Valour, loyalty and sacrifice!

Baji Prabhu Deshpande was one of the most able lieutenants of Shivaji. He sacrificed his life defending Shivaji in a heroic last stand known as the "Battle of Pavan Khind" in which his force was hugely outnumbered.(1)

In this battle he became a martyr, but managed to halt the enemy forces for several hours, which secured Shivaji’s safety and victory on another front. Without this heroic last stand Shivaji’s glorious career may have been cut short.(2)

Baji Prabhu was senior to Shivaji. In the beginning he opposed Shivaji being from a rival Maratha clan, but realised that Shivaji stood for national resurgence. Henceforth he became a friend and loyal supporter of Shivaji.(3)

In 1660, Shivaji was trapped in the fort of Panhala, under siege and vastly outnumbered by an Adilshahi army led by general Siddhi Jauhar.(4)

$Vibhu Vashisth \U0001f1ee\U0001f1f3$

Vibhu Vashisth 🇮🇳...
@VIBHU_Tweet

Did you know?

Rani Bhabani was the Queen of Natore, Bengal or 'Natorer Rani' as she was famously called. She made great contributions in Tarapith & renovated Benaras.

In Varanasi, Durga Kund Mandir was constructed by Rani Bhabani in the 18th century.

Born in Chhatimgram village, Bogra District,Her father's name was Atmaram Choudhury.Bhabani was married off to Raja Ramkanta Moitra,the then zamindar of Rajshahi.After his death, Bhabani became the zamindar, and started being referred to as Rani.She was known as Ardhabangeshwari.

A woman as a zamindar was extremely rare in those days, but Rani Bhabani managed the vast Rajshahi zamindari most efficiently and effectively for over four decades.
Maharani Bhavani was very pious in her personal life. She passed her life in a strict disciplined way.

She conducted the administrative work skillfully. As a Maharani she was an impartial judge. Rani Bhavani had a very hard time during the fag end of her life. The Zamindari (estate) incurred serious loss due to the change of the revenue policy of the company.

In spite of being the owner of a large Zamindari (estate), she had to depend on the stipend of the government in the later part of her life. The amount of this stipend gradually decreased and became Rs. 1000/- only in the end.

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Anshul Pandey
@Anshulspiritual

THE NOTICEABLE SIGNS OBSERVED ON IMPENDING DEATH(मृत्यु के संकेत या चिन्ह)

As per Skanda Puran, Kartikeya had narrated to Muni Agastya about the signs of the coming death. This is as per this ancient scripture.

If one experiences the air coming out of right nostril continuously then it is observed that the person dies within three years. If the breathing is continuous towards upper side from both the nostrils, then the person can die within two three days.

If the breathing is through the mouth instead of the nostrils then the person may live only for two days. The person should take into coignance these signs of the occurance of any sudden death.

As per astrology when the Surya is in the 7th house and Chandrama is in its own house and the breathing is only through the right nostril then the danger exists. If you see a yellow black coloured figure who becomes invisible immediately then the life span is limited to 2 years.

If any person sneezes, passes urine, stool and semen all together he has only a year more to live. If a person sees blue coloured snakes flying in the sky then he has only six more months to live. If a person sees any thing opposite to its real self like colours

$\u2745\u1710\u170b\u1713\u170e$

❅ᜐᜋᜓᜎ...
@uglyluhan

First thread of the year because I have time during MCO. As requested, a thread on the gods and spirits of Malay folk religion. Some are indigenous, some are of Indian origin, some have Islamic

i wonder if you can make a thread bout witchcraft in malaysia.. or list of our own local gods/deites..
— r a y a \U0001f319 (@lcvelylilith) February 20, 2020

Before I begin, it might be worth explaining the Malay conception of the spirit world. At its deepest level, Malay religious belief is animist. All living beings and even certain objects are said to have a soul. Natural phenomena are either controlled by or personified as spirits

Although these beings had to be respected, not all of them were powerful enough to be considered gods. Offerings would be made to the spirits that had greater influence on human life. Spells and incantations would invoke their

Animist ceremonies of a religious or magical nature were normally held for the purpose of divination or making a request. This would either be done at a keramat or at a shrine similar to the Thai spirit houses or Chinese roadside shrines pic.twitter.com/I1hliyi0x3
— \u2745\u1710\u170b\u1713\u170e (@uglyluhan) June 16, 2019

Two known examples of such elemental spirits that had god-like status are Raja Angin (king of the wind) and Mambang Tali Arus (spirit of river currents). There were undoubtedly many more which have been lost to time

Contact with ancient India brought the influence of Hinduism and Buddhism to SEA. What we now call Hinduism similarly developed in India out of native animism and the more formal Vedic tradition. This can be seen in the multitude of sacred animals and location-specific Hindu gods

Novid Houellebecq (Tha...
@GarouGothic

I want to explain what happened to tumblr overnight. And why Twitter as reached it's dream (or have come ever so close to it)

Yahoo, who bought Tumblr years ago, used to have a huge adult presence on the early net. They allowed adult groups and what not.

However, people and bots (just like now) misused the service, and Yahoo were forced to make a choice. They made private the groups (and later closed them down and sold some of it to other companies) and then ended their chatrooms on yahoo messenger...

after a incident with one of the chatrooms vid cams. The damage was done, Yahoo Messenger lost a lot of people - and with the closing of the groups - backpage and Craigslist came more important.

Now backpage is no more and Craigslist is slowly passing away. Tumblr had a semi strong community, but once 2014 came around and both porn, and political bots exploded the quality started to go down,