BC MACHINE LEARNING

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Caio Rolla
@caio_rolla 5 years, 9 months ago 819 views

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Starting a new project using #Angular? Here is a list of all the stuff i use to launch my projects the fastest i can.

A THREAD 👇

Have you heard about Monorepo? I created one with all my Angular (and Nest) projects using https://t.co/aY5llDtXg8.

I can share A LOT of code with it. Ex: Everytime i start a new project, i just need to import an Auth lib, that i created, and all Auth related stuff is set up.

Everyone in the Angular community knows about https://t.co/kDnunQZnxE. It's not the most beautiful component library out there, but it's good and easy to work with.

There's a bunch of state management solutions for Angular, but https://t.co/RJwpn74Qev is by far my favorite.

There's a lot of boilerplate, but you can solve this with the built-in schematics and/or with your own schematics

Are you not using custom schematics yet? Take a look at this:

https://t.co/iLrIaHVafm
https://t.co/3382Tn2k7C

You can automate all the boilerplate with hundreds of files associates with creating a new feature.

i18n Part 1:

You can find a lot of solutions for i18n (internacionalization) for Angular, but the best one is the "native". All you need to do is mark all traslatable text with the "i18n" attribute and translate the .xlf files created by the Angular CLI.

i18n Part 2:

I recommend ngx-dy-i18n for translations during execution and xliffmerge (ngx-i18nsupport) to control the translations files. You can use NGINX to redirect the user to it's language version.

https://t.co/g6Omudp7RZ
https://t.co/JXpoGlRh6l
https://t.co/4u9tXL8A7w

@fontawesome has a hell of a library to work with it's icons on Angular, and the free version is good enough for 99% of cases. I think it's bigger (and better) than Angular Material icons module.

Need a Rich Text Editor? Try ngx-quill. It's a wrapper for the Quill text editor.

https://t.co/0NUJOED4xX
https://t.co/jEB10XXWJL

Image cropper? Try ngx-image-cropper

https://t.co/TDvyWin7ft

A really nice article:

Sustainable Angular Architectures. A three parts article by @ManfredSteyer

https://t.co/Pr9aH42rua

Written on @typefullyapp.

Give you recommendation on Articles, Libraries and Practices 👇

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Pratham Prasoon
@PrasoonPratham

Here's everything you need to know about the math for machine learning.

(+ free resources )
🧵👇

Before diving into the math, I suggest first having solid programming skills.

For example👇

(2 / 18)

In Python, these are the concepts which you must know:

- Object oriented programming in Python : Classes, Objects, Methods
- List slicing
- String formatting
- Dictionaries & Tuples
- Basic terminal commands
- Exception handling

(3 / 18)

If you want to learn those concepts for python, these courses are freecodecamp could be of help to you.

🔗Basics:youtube∙com/watch?v=rfscVS0vtbw
🔗Intermediate :youtube∙com/watch?v=HGOBQPFzWKo

(4 / 18)

👉You need to have really strong fundamentals in programming, because machine learning involves a lot of it.

It is 100% compulsory.

(5 / 18)

Pratham Prasoon
@PrasoonPratham

There are several skills needed for learning machine learning that no one talks about.

Here are some of them.
(from what I've learned over the past two years)
🧵👇

This thread aims to introduce to you some of the skills often ignored for learning machine learning but are actually very important.

These skills will enable you to learn concepts quickly and more efficiently in this field.

(2 / 9)

1⃣ Reading

Probably one of the most underrated skills on this list.

In machine learning, you HAVE to read a lot of articles, papers, documentation, and whatnot.

It is mostly due to the theoretical nature of this field that reading is an important skill to have.

(3 / 9)

2⃣ Strong fundamentals in programming

Machine learning is just a lot of programming mixed with math and data.

Having clear programming fundamentals is crucial for this field.

I highly suggest you learn about these if you are using Python for machine learning.👇

(4 / 9)

- Object oriented programming in Python :Classes, Objects, Methods
- Lists & List functions
- Dunder Methods
- List comprehension
- List slicing
- String formatting
- List, Dictionaries & Tuples
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(5 / 9)

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Pratham Prasoon
@PrasoonPratham

Which libraries do you really need to get started with Machine Learning and why?

🧵👇

First and foremost, make sure that you have nailed the fundamental concepts of Python because machine learning requires a lot of programming!

(2 / 19)

If you know these topics, then you are good to go with machine learning in Python

- Object-oriented programming in Python:Classes,Objects,Methods
- Lists & List functions
- List comprehension
- List slicing
- String formatting
- List,Dictionaries & Tuples

(3 / 19)

Now, let's understand what popular python machine learning libraries do.

We will talk about👇
- TensorFlow (+ Keras)
- PyTorch
- Pandas
- Numpy
- Matplotlib
- SciKit Learn
- Seaborn

(4 / 19)

Now let's cover the libraries that you have to learn (at least the basics) for machine learning

1. Pandas

Pandas is a python library that allows you to store and read data from spreadsheets ( .csv, .xlsv files ) in structures called Dataframes.

(5 / 19)

Anson Horton
@AnsonHorton

1/ @werat asked about whether the debugger was using the C# compiler or language service in VS 2002. It was not. The debugger has a component called an ‘expression evaluator’ that is provided per language and is responsible for parsing and evaluating expressions when stopped at a

2/ breakpoint. For example, if you type into the immediate window, hover over a variable, type into the watch window, etc. the expression evaluator is involved. The debugger and the language service are actually deeply integrated in a number of scenarios in VS, which may

3/ initially seem surprising. I may talk about more of these scenarios in the future, but to give a flavor, when you set a breakpoint at design time the language service is involved, when you are using Edit and Continue the LS is involved, the range of what is being evaluated

4/ when you get a debugger data tip, completion lists when typing in the data windows or immediate window, etc. Prior to VS 2002, there were distinct debug environments tailored to each target customer (VB/VBA, C++, VJ, VBScript, TSQL, FoxPro, Fortran, etc.). The goals of the

5/ VS 2002 debugger included unifying the debugger backend components and providing a single UI stack that would enable new scenarios (for example, a callstack across languages). Expression evaluators are the architecture that separate the language specific pieces from the

Santiago
@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?

👇

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She joined the freedom struggle in the present-day Northeast India. Today, her struggle is lost in history as most of her countrymen wouldn’t even have heard her name. B'coz our history textbooks tell us that only Mahatma Gandhi &Pandit Nehru got India its Independence.

At 16 yrs of age, this valiant girl was sentenced to life imprisonment for leading a movement to drive out the colonial rulers from Manipur and Nagaland. Nevertheless, she was released in 1947 after India’s independence and was given the title ,"Rani of Nagas".

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According to psychologists, there are four types of intelligence:

- Intelligence Quotient (IQ)
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- Adversity Quotient (AQ)

1. IQ is the measure of one's ability to comprehend, solve maths; memorize things & recall subject matters.

2. EQ is the measure of your ability to maintain peace with others; keep to time; be responsible; be honest; respect boundaries; be humble, genuine, and considerate.

3. SQ is the measure of one's ability to build a network of friends & maintain it over a long period of time.

4. AQ is the measure of your ability to go through a rough patch in life and come out without losing your mind. It is a new paradigm and can be used to determine who will give up in face of troubles and may abandon their families.

Now to the very interesting & analytical part👇

People that have higher EQ & SQ tend to go further in life than those with high IQ but low EQ &SQ.

Most schools capitalize on improving IQ level while EQ & SQ are played down.

A man of high IQ can end up being employed by a man of high EQ & SQ even though he has an average IQ.

Your EQ represents your character; your SQ represents your charisma. Give in to habits that will improve these three Qs but more especially your EQ and SQ.

EQ and SQ make one manage better than the other.

Try not only to have a higher IQ but also to have higher EQ and SQ.

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India had a well developed education system centuries before the westerners arrived and called us uncivilized. Education was always given a great importance in Indian civilisation since times immemorial.

Ancient India had the Gurukulas and Ashramas as the epicentres of the knowledge and enlightenment. Bigger Gurukulas served as the centres of higher education called universities. Besides these universities, temples also emerged as the major learning centres.

Studying the Holy Scriptures, character building, personality development, responsibilities towards self,family and society,discipline and preservation of the ancient culture and heritage were the key embodiments of education.

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NALANDA UNIVERSITY
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2. The heritability of IQ *increases* from childhood to adulthood. Meanwhile, the effect of the shared environment largely fades away. In other words, when it comes to IQ, nature becomes more important as we get older, nurture less. https://t.co/UqtS1lpw3n

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4. IQ predicts many important real world outcomes.

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